bluuebunny/crossref_metadata_2025_split huggingface dataset:
OML‐Combine: Online Machine Learning tool for Combining datasets to increase power and facilitate multi‐centre collaboration on Alzheimer's disease studies
Authors: Christodoulides Chris Dalas , Canovas Rodrigo , Dore Vincent , Doecke James D. , Laws Simon M , Weiner Michael W , Rowe Christopher C. , Villemagne Victor L , Masters Colin L. , Fripp Jurgen , Maruff Paul , Shishegar Rosita 
Published: January 2025

AbstractBackgroundDiagnostic and prognostic decisions about Alzheimer’s disease (AD) are more accurate when based on large data sets. We developed and validated a machine learning (ML) data harmonization tool for aggregation of prospective data from neuropsychological tests applied to study AD. The online ML‐combine application (OML‐combine app) allows researchers to utilize the ML‐harmonization method for harmonization of their own data with that from other large available data bases (e.g. AIBL) to enable development of their own neuropsychological models of AD.MethodThe OML‐Combine application implements an established neuropsychological test data harmonization method1 based on non‐parametric multivariate imputation using random forests (missForest)2. Test data not included in a cohort is classified as missing and imputed using known data from the cohort based on information known from other studies1. A web‐based R‐Shiny application was developed to facilitate harmonization of data from different cohorts and visualise outcomes. OML‐combine also calculates percentages of missing values for each test score across the pooled dataset allowing decisions about the validity of harmonized data. OML‐combine also allows harmonization of multiple datasets simultaneously.ResultThe R Shiny package was used to produce an interactive data harmonization tool. Figure 1 displays the interface, showing results from an example harmonization and validation step using simulated data from AIBL (N=1813) and ADNI (N=1945). In the validation tab, users are provided with a figure of the distributions of both raw and harmonized datasets, including predicted test scores and an accuracy measurement for each score. These can be used to validate the outcomes and compare them to known relationships established from the raw data for each dataset.ConclusionOML‐Combine facilitates the harmonization of neuropsychological test data from established AD cohort studies. Visualization of predicted test scores and the original data sets can thereby assist with decisions about accuracy of harmonized data and can provide a basis for adjustment of inputs to optimize models. This allows researchers to combine their own data with that from other currently available studies to improve diagnostic and prognostic models of AD.References:1doi: 10.1002/alz.0443022doi:10.1093/bioinformatics/btr597
Blood‐based biomarkers for Alzheimer’s disease among ethnoracial minority samples – a scoping review
Authors: Osse Amanda Leisgang , Nguyen Amy , Moeller Stacey , Cummings Jeffrey L. , Kinney Jefferson W , John Samantha E 
Published: January 2025

AbstractBackgroundApproximately 6.7 million Americans, aged 65 and older, are living with Alzheimer’s disease (AD) dementia. Ethnoracial minority populations are at greater risk for AD. Black/African Americans (B/AA) are twice as likely than non‐Hispanic White (NHW) individuals to develop AD, and Hispanic/Latinos (H/L) are 1.5 times as likely. Accurate, timely, and accessible diagnosis of AD is limited. The use of blood‐based biomarkers (BBB) could improve treatment and care among ethnoracial groups at risk.MethodWe performed a scoping review of the literature to summarize the current state of BBB research in B/AA and H/L populations. Searches through three databases (PubMed, APA PsycInfo, and Scopus) yielded 383 and 281 papers for B/AA and H/L populations, respectively. Papers were evaluated through title/abstract, followed by full paper review, and included in the final sample if plasma, serum, or whole blood biomarkers were collected in B/AA and H/L samples with pathological or cognitive evidence of AD etiology.ResultsOverall, 19 B/AA (sample size range N=76‐5,228) and 30 H/L (sample size range N=51–3071) papers published between 1999 and June 1, 2023 met criteria. Publications evaluating ethnoracial minority samples increased over time and particularly in recent years (Figure 1). Studies included samples primarily from the United States, with majority of B/AA studies conducted in the eastern U.S., and majority of H/L studies conducted in Texas (Figure 2). We classified biomarkers into five categories, AD pathologies (amyloid, tau, neurodegeneration [ATN]), cardiovascular, inflammatory, metabolic, and unspecified. Studies evaluating ATN in both H/L and B/AA increased over time, with multiplex assays and Quanterix Simoa the most frequently used methods.ConclusionThere has been a progressive increase in investigations of BBB for AD across all ethnoracial groups. Consideration of the blood sample measured, demographics of the individuals included, and location of the studies is required. Standardization of methods used and biomarkers evaluated, as well as replication of studies across larger and broader samples are needed to allow reliable conclusions to be drawn. Better understanding of BBB of AD in H/L and B/AA populations would advance the diagnosis and treatment of AD in these at‐risk ethnoracial groups.
Validation of QyScore® White Matter Hyperintensity (WMH) U‐Net segmentation algorithm against expert manual consensus and comparison with currently available state‐of‐the‐art methods
Authors: Gordon Elizabeth , Villa Luca , Guizard Nicolas , Tran Philippe 
Published: January 2025

AbstractBackgroundDetection and quantification of White Matter Hyperintensities (WMH) are clinically important across multiple CNS disorders and neurodegenerative dementias. However, the prohibitively labor‐intensive nature of manual segmentation limits widespread clinical application. Accurate automated methods for segmenting WMH are needed to overcome this unmet clinical need.MethodThe validation cohort consisted of 129 individuals who had undergone T1‐weighted and T2‐FLAIR MR imaging. To ensure robust results, different scanners (30 GE, 26 Philips, 73 Siemens) and varied patient populations (including Alzheimer’s Disease (n=49), Frontotemporal dementia (n=5) and Multiple Sclerosis (n=45)) were included (Table 1A). The WMH_U‐Net algorithm included in QyScore®, an FDA‐approved and CE‐marked neuroimaging platform, automatically segmented WMH in each image set. These were compared to the gold‐standard consensus of three expert neuroradiologist manual segmentations. Next, a direct comparison of QyScore® WMH_U‐Net was run with six state‐of‐the‐art supervised and unsupervised segmentation methods (LST‐LGA and LPA, Lesion‐TOADS, lesionBrain, BIANCA and nicMSlesions) on a dedicated MS dataset (Table 1B) with default and optimized settings were available. Performance metrics included spatial overlap (Dice Similarity Coefficient (DSC) and F1 scores) and volume comparisons (intra‐class correlation coefficient (ICC) and absolute volume error (AVE, ml)).ResultQyScore® WMH_U‐Net demonstrated good volume and spatial overlap (average DSC=0.66±0.2), especially with larger WMH load (15‐30ml: DSC=0.75±0.07) across the validation cohort. Optimizing and/or retraining LST‐LGA, BIANCA and nicMSlesions, improved their performances substantially; however, QyScore® WMH_U‐Net remained comparable with the optimized nicMSlesions, with better performance than the optimized LST‐LGA and BIANCA. Friedman test (ANOVA) revealed significantly better spatial (DSC: p=5.90x10‐21) and volumetric agreement (AVE: p=3.61x10‐6) between QyScore® WMH_U‐Net and the other methods (default settings). Wilcoxon signed‐rank post‐hoc analysis (Bonferroni corrected: p<0.0071) demonstrated QyScore® WMH_U‐Net significantly outperformed all methods for spatial and volumetric agreement (Table 2).ConclusionQyScore® WMH_U‐Net produced, robust and the most accurate WMH segmentations across multiple scanners and patient groups, supporting its widespread application for clinical routine practice. It is because it is using a U‐Net approach which is understood to be a fast method for image segmentation over more conventional computer vision methods.
The role of immune dysregulation of innate and adaptive immune cells in the prodromal and clinical stages of Parkinson’s disease
Authors: Mark Julian R , Wallings Rebecca L , Staley Hannah , Tansey Malu Gámez 
Published: January 2025

AbstractBackgroundPeripheral blood mononuclear cells (PBMCs) were obtained from patients across different stages of Parkinson’s disease (PD) progression and stimulated ex vivo to develop biomarkers for predicting PD progression.MethodPBMCs obtained at one time‐point from patients with moderate stage PD (>5 years after diagnosis) (n = 30), early stage PD (<5 years after diagnosis) (n = 27), prodromal PD (rapid‐eye‐movement sleep behavior disorder patients) (n = 14), and healthy controls (HCs) (n = 9) were isolated from whole blood and cryopreserved. Samples were thawed, then pan‐monocytes and T‐cell populations were isolated from PBMCs and subjected to treatment with vehicle or IFN‐γ. An additional treatment condition with CD3/28 magnetic beads was included for T‐cells. Cultured media was kept for evaluation of cell‐type specific cytokine release, and live cells were analyzed with flow cytometry for markers of immune activation, mitochondrial and lysosomal function, and LRRK2 expression and activity.ResultIn classical, intermediate, and non‐classical monocytes from HCs, expression of pRab10, LRRK2, and MHC‐II increases after treatment with ex vivo IFN‐γ stimulation. In CD4+ and CD8+ T‐cells from HCs, IFN‐γ and CD3/28 bead treatment caused increased expression of pRab10. CD3/28 magnetic beads, but not IFN‐γ, caused increased expression of CD137 and LRRK2, while also leading to reduced levels of acidified lysosomes. Studies are currently underway to analyze cells from PD and prodromal patients and evaluate cell‐type specific cytokine release in the conditioned media.ConclusionWe have applied a validated ex vivo stimulation protocol using PBMCs from PD patients across different stages of disease to measure immune cell activation and cell‐type specific cytokine release. If our hypothesis is correct, we expect that immune cell subsets from PD patients will display a signature of dysregulated immune response to stimulation. Furthermore, we expect that prodromal PD patients will exhibit dysregulated peripheral immune responses compared to controls, including altered mitochondrial and lysosomal function and cytokine release.
Synapse loss in early‐ and late‐onset Alzheimer's Disease assessed by 18F‐SynVest‐1
Authors: he kun , Xie Fang , Huang Qi 
Published: January 2025

AbstractBackgroundWe aimed to investigate the loss of synaptic density in early‐onset and late‐onset Alzheimer's Disease.MethodOne hundred and eighty‐two participants underwent synaptic density PET with 18F‐SynVesT‐1. Including 23 early‐onset Alzheimer‘s Disease (EOAD), 58 late‐onset Alzheimer's Disease (LOAD), 16 EOnonAD, 28 LOnonAD, 31 younger normal control (age < 65) and 26 older normal control (age ⩾ 65). We analyzed the synaptic density loss in EOAD and LOAD relative to their control group respectively. Associations between age and synaptic loss were evaluated in different groups.ResultEOAD and LOAD groups both displayed significant synaptic density across most areas of cerebrum cortex. Relative to LOAD group, EOAD group showed severer synaptic loss in Lateral Parietal lobe. In EOAD group, synaptic density in occipital lobe had positive association with age. While, in LOAD group, synaptic density in most areas of the cerebrum cortex had a negative association with age.ConclusionOur study suggested that the areas of synaptic loss were different between EOAD and LOAD.
The associations between sleep disturbances and allostatic load, and the role of sex, beta amyloid, and burnout history in a memory clinic sample: the Co‐STAR study
Authors: Adedeji Dickson Olusegun , Holleman Jasper , Kåreholt Ingemar , Solomon Alina , Kivipelto Miia , Sindi Shireen 
Published: January 2025

AbstractBackgroundSeveral studies have investigated the link between sleep disturbances and allostatic load (AL), but the results are varied, and less is known about the associations in clinical samples. The goal of this study is to assess the associations between sleep disturbances and AL among memory clinic participants, and to examine differences according to sex, beta‐amyloid status and history of burnout status.MethodThe study was based on 146 memory clinic participants diagnosed with either Mild Cognitive Impairment (MCI) or Subjective Cognitive Impairment (SCI) in the Cortisol and Stress in Alzheimer’s Disease Study (Co‐STAR) (Sweden). Self‐reported sleep was measured using the Karolinska Sleep Questionnaire (KSQ). The AL index is a measure of chronic stress including blood‐based markers reflecting the neuroendocrine, immunological, metabolic, and cardiovascular systems, constructed using 16 biomarkers. Beta‐amyloid was measured from cerebrospinal fluid samples. History of burnout was self‐reported. Linear regressions were conducted to assess the associations between sleep disturbances and allostatic load, while adjusting for age, sex and sleep medications.ResultLower total sleep score (b=‐0.228, p= 0.028) and sleep apnea index (b=‐0.187, p= 0.046) correlated with higher AL index. In stratified analyses, lower total sleep score was associated with higher AL index in women (b=‐0.282, p= 0.049), while higher insomnia levels (b=‐0.295, p= 0.038) were linked to lower AL levels in men. AL was only associated with daytime sleepiness in participants with normal beta‐amyloid levels, where a lower daytime sleepiness score (b=‐0.298, p= 0.038) was linked to higher AL levels. Among those without a history of burnout, higher AL index correlated with lower total sleep score (b=‐0.249, p= 0.045), insomnia score (b=‐0.223, p= 0.045), difficulty waking up score (b=‐0.225, p= 0.038), and non‐restorative sleep index (b=‐0.221, p= 0.043).ConclusionThis study shows varied associations between sleep disturbances and across different subgroups, highlighting the roles of age, sex, beta‐amyloid levels, and history of burnout in the associations. It may be of valuable importance to consider AL when evaluating sleep disturbances and implementing lifestyle interventions for the reduction of chronic stress and sleep disturbances to reduce the risk of cognitive decline.
Risk factor, neuropathological, and clinical correlates of perivascular spaces in brain donors exposed to repetitive head impacts
Authors: Mosaheb Sydney , Rodriguez Frances , Abdolmohammadi Bobak , Uretsky Madeline , Nowinski Christopher , Daneshvar Daniel H , Tripodis Yorghos , Martin Brett , Palmisano Joseph N. , Farris Chad , Huber Bertrand Russell , Stein Thor D. , McKee Ann C. , Mez Jesse , Romero Jose Rafael , Alosco Michael L. 
Published: January 2025

AbstractBackgroundEnlarged perivascular spaces (ePVS) on MRI can signal impaired cerebral fluid clearance and predict dementia risk. Risk factors and biological correlates of ePVS are uncertain partially due to the lack of pathological correlation studies. Repetitive head impacts (RHI) from contact sports might represent one risk factor for ePVS, given their association with vascular pathologies and chronic traumatic encephalopathy (CTE), a neurodegenerative disease characterized by perivascular p‐tau aggregates. We examined risk factors, neuropathological, and clinical correlates of antemortem MRI ePVS among brain donors exposed to RHI.MethodThe sample included 104 brain donors exposed to RHI from the UNITE brain bank. Clinical MRIs were obtained through medical record requests. A stroke neurologist used established visual rating scales (0=no ePVS, 4= >40 ePVS) to rate ePVS in the centrum semiovale (CS‐ePVS) and basal ganglia (BG‐ePVS) on axial T2 (n=11, 10.6%) or T1 (n=93, 89%). ePVS were coded as low (1/2) or high burden (3/4). Neuropathological diagnoses were made using established criteria. Years of football served as a proxy for duration of RHI. Antemortem dementia diagnoses were made through consensus conferences. Regression‐based analyses tested the association between ePVS with years of football play, various neuropathologies, dementia status and FAQ. Analyses controlled for years from MRI scan to death.ResultSample characteristics are in Table 1. The most common pathological diagnosis was CTE (n=71, 68%). 34 (32.7%) and 13 (12.5%) had high CS‐ePVS and BG‐ePVS burden, respectively. More years of football play was associated with greater CS‐ (OR=1.12, 95% CI=1.03‐1.22, p=0.01) and BG‐ePVS (OR=1.12, 95 CI=1.01‐1.24, p=0.03). Effect sizes remained when age at MRI was included for both CS‐ and BG‐ePVS (OR=1.09) but statistical significance was diminished. Greater CS‐ePVS was associated with more severe CTE, arteriosclerosis, atherosclerosis, cerebral amyloid angiopathy and Lewy body disease (Table 2). BG‐ePVS was only associated with arteriosclerosis. Greater CS‐ePVS were associated with increased odds for having dementia diagnosis (OR=5.41, 95% CI=1.42‐20.54, p=0.01). Clinical and pathological correlations were not statistically significant when age at MRI was included.ConclusionEnlarged PVS might be long‐term MRI consequences of exposure to RHI, but their age independent pathological and clinical correlates in this setting remain uncertain.
The Cerebellum Plays a Protective Role in Cognitive Aging and Disease: Insights from a Multi‐Cohort Study
Authors: Uquillas Federico d’Oleire , Sefik Esra , Seidlitz Jakob , Merriman Jewel , Zhang Veronica , Kislin Mikhail , Cohen Jonathan D , Alexander‐Bloch Aaron , Bethlehem Richard A.I. , Sepulcre Jorge , Wang Samuel S.‐H. , Vannini Patrizia , Gomez Jesse ,   the Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

AbstractBackgroundStudying brain reserve — the brain’s resilience to age‐related changes or damage — is crucial for understanding protective mechanisms against cognitive decline. The cerebellum may be a key region in brain reserve, but it has been historically understudied. This investigation delves into this critical area within the largest aging multi‐cohort to date.MethodsData were sourced from the Human Connectome Project‐Aging (n=708, 36‐100yrs), UK Biobank (n=45,013, 44‐81yrs), and ADNI (n=1,441, 56‐95yrs). ADNI participants were cognitively normal, had mild cognitive impairment, or Alzheimer’s disease (AD) dementia. We examined associations between cerebellar tissue volume, age, Montreal Cognitive Assessment (MOCA) scores, global PET amyloid burden, and APOE genotype. Statistical models included sex and estimated intracranial volume (eTIV) as covariates, with adjusted household income considered when available.ResultsSpatial analysis of HCP‐Aging data revealed that aging unfolds heterogeneously across the cerebellum; posterior portions of the cerebellum (Crus I) showed greater effects than anterior regions (Lobule I‐III) (Bonferroni‐corrected, p<0.05). MOCA scores were associated with higher tissue density in the cerebellum (p<0.0001), as much as neocortex, and MOCA scores coupled most strongly with posterior cerebellar cortex, overlapping frontoparietal, ventral attention, and default mode network representations. Strikingly, greater volume in this MOCA‐related cerebellar cortex signature protected against aging‐related cognitive decline (p=0.029). We validate tissue aging results in the UK Biobank – again, posterior cerebellum demonstrated the greatest aging effect (p<0.0001), and individuals with greater cerebellar volumes showed less decline in processing speed and executive function (Trails Making‐B time: p=0.001; Digit Symbol Substitution score: p=0.038). Across all ADNI diagnostic groups, AD patients with low amyloid‐beta burden (Aβ‐) exhibited the strongest cerebellar association with MOCA (volume x group, Aβ‐ AD: p=0.00004). In Aβ‐ individuals, APOE genotype interacted with cerebellar volume on MOCA, with ε4/ε4 carriers showing the greatest effect (volume x APOE, ε4/ε4: p=0.017).ConclusionsOur large‐scale study demonstrates the cerebellum’s critical role in mitigating patterns of cognitive decline. This protection persists until significant amyloid burden, especially in APOE ε4/ε4 carriers, reshaping our understanding of reserve and AD risk. The cerebellum’s integral contribution to brain reserve has substantial implications for aging populations and should be a focus of future clinical research.
Does the association between white matter hyperintensity severity and Alzheimer’s disease indicate a primary role of cerebrovascular disease in Alzheimer’s disease pathogenesis?
Authors: Brickman Adam M. 
Published: January 2025

AbstractWhite matter hyperintensities (WMH) are areas of increased lucency visualized on T2‐weighted magnetic resonance imaging (MRI), including fluid attenuated inversion recovery (FLAIR) sequences. Over the past 15 years we have been examining WMH in studies of cognitive aging among clinical, community‐based, and populations at genetic risk to understand the role of vascular brain injury in Alzheimer’s disease (AD) onset, symptom progression, and pathogenesis. Our findings suggest that regional WMH, particularly when distributed in posterior areas, increase risk for clinical AD and contribute to the clinical course of the disease, even among genetic population with relatively low rates of vascular risk factor, like adults with Down syndrome and with autosomal dominant genetic mutations for AD. While these observations suggest a role of endogenous cerebrovascular disease as a driver or core feature of AD, there has been considerable discussion about the underlying pathophysiology of WMH. Some authors argue that WMH in the context of AD reflect white matter changes secondary to neurodegeneration (so‐called “Wallerian degeneration”). We have argued against this possibility based on four observations. First, experimental data from animal models of vascular brain injury suggest that hypoperfusion injury gives rise white matter injury and downstream tau pathology and neurodegeneration. Second, the anatomical distribution of WMH in AD more closely aligns with the brain’s perfusion patterns and the vulnerability of whatershed regions to changes in blood supply and small vessel injury than with proximity to cortical neuronal injury. Third, the temporal evolution of WMH in the context of AD suggests a contribution of WMH that precedes expected neurodegenerative changes. Finally, we do not view an observed relationship between WMH and risk factors, such as hypertension, as a requirement to establish a cerebrovascular basis of WMH; rather, in total, findings suggest an “endogenous” cerebrovascular component, perhaps mediated by inflammatory changes, genetics, or blood brain barrier breakdown. Understanding the pathophysiological basis of WMH with respect to underlying vasculature may point to novel directions for disease prevention or intervention.