bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data harmonization across eight publicly available longitudinal studies of aging, neurodegeneration and dementia
Authors: Low Kevin , Nourollahimoghadam Elnaz , Nir Talia M , Vargas Hernan , Nguyen Uyen , Shetty Ankush , Xiao Cally , Neu Scott C. , Crawford Karen , Thomopoulos Sophia I , Thompson Paul M , Salminen Lauren , Toga Arthur W. , Pappas Ioannis , Jahanshad Neda 
Published: December 2023

AbstractBackgroundLarge‐scale multi‐study analyses are required to ensure reproducibility, reliability and generalizability in mapping neurodegeneration and risk for ADRD. However, the heterogeneity in data collection paradigms can complicate and confound data pooling; data harmonization is essential. Longitudinal studies add to the complexity of harmonization as a variety of follow‐up time points and time encoding schemes are used. Here, we pool data from 8 publicly available longitudinal neuroimaging studies on neurodegeneration and dementia to highlight differences in: 1) diagnostic categorization of controls, and people with mild cognitive impairment, and dementia; 2) the extent of follow‐up visits across neuroimaging and clinical assessments; and 3) encodings of various meta‐data elements including scanner manufacturer, sex, and handedness. To allow a systematic approach to multi‐study dementia research, we propose an initial ontological framework for longitudinal data archival and retrieval, capable of capturing similar data elements within given themes while ensuring that unique differences across studies are retained.MethodAIBL, ADNI‐1, ADNI2/GO, ADNI‐3, OASIS‐2, OASIS‐3, PREVENT‐AD, and MIRIAD, were accessed. Study designs, inclusion and exclusion criteria, and downloaded data elements were used to describe diagnostic criteria, imaging data, demographic features, and longitudinal data collection schemes. We create common terms to map data elements across studies, and a consistent naming scheme for longitudinal data.ResultFigure 1 shows the breakdown of diagnostic labels per cohort, and highlights how different cognitive labels may be assigned to people with the same performance scores, for example, on the Mini Mental State Examination (MMSE). Figure 2 highlights the differences in longitudinal data collection schemes across cohorts, and in labels of commonly collected elements. Using common terms provided an easy way to simultaneously query data across all studies, while retaining a map back to the original terms. Figure 3 showcases our proposed naming scheme for capturing longitudinal data elements using a relational ontological framework. This framework successfully harmonized data across study demographics, timepoints, and imaging properties.ConclusionMulti‐study data analyses are becoming common practice thanks to large scale efforts such as ENIGMA and GAAIN. Harmonization of meta‐data across studies will allow for efficient pooling of data for tracking disease progression and related risk over time.
Estimating the time between amyloid and tau‐PET positivity: Implications for Alzheimer’s disease prevention trials
Authors: Moscoso Alexis , Heeman Fiona , Dunås Tora , Schöll Michael 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) is characterized by a preclinical stage in which abnormal accumulation of amyloid‐β (Aβ) leads to phosphorylated tau aggregation. This sequence of events represents the transition between “AD pathologic change” (A+T‐) to the much riskier full AD neuropathology (A+T+, Jack et al. Alzheimers Dement. 2018). Thus, to understand the clinical relevance of the A+T‐ stage in the long term, it is important to understand the temporal course of Aβ and tau. In this study, we used longitudinal Aβ‐ and tau‐positron emission tomography (PET) to estimate the expected time gap between Aβ‐ and tau‐PET positivity, and explored factors that influenced this gap.MethodWe estimated the natural history of amyloid accumulation in AD using longitudinal Aβ‐PET data from 1690 AD‐continuum subjects from the ADNI. Specifically, we fitted a non‐linear mixed effects model (3‐knot spline) and modelled the subject‐specific “age of Aβ positivity” as random effects (Figure 1). An interval‐censored time‐to‐event analysis using “time to amyloid positivity” as time variable was performed on 318 Aβ+ ADNI participants who had available tau‐PET ([18F]flortaucipir) visual reads. Cox proportional hazards regression was used to assess whether age of onset of amyloid positivity, sex, APOE status, and cognitive impairment at follow‐up influenced the onset of tau‐PET positivity relative to Aβ‐positivity.ResultAfter ∼11 years from Aβ positivity, 50% of the CU individuals progressed to tau‐PET positivity, while only ∼17% remained tau‐PET negative after 20 years (Figure 2). Among the studied factors, only the presence of cognitive impairment accelerated the onset of visual tau‐PET positivity (HR = 2.52, p<0.001, median tau‐free survival difference ∼6 years) (Figure 3). Both female sex (HR = 1.44, p = 0.16, median tau‐free survival difference∼2.5 years) and presence of the APOE‐ε4 allele (HR = 1.44, p = 0.15, median tau‐free survival difference∼2.5 years) were trend‐level associated to faster onset of tau‐PET positivity.ConclusionThe time gap between Aβ‐ and tau‐PET positivity typically spans a decade and is highly variable across individuals. This long gap implies that a significant fraction of A+T‐ CU older individuals will never develop tau‐PET positivity and subsequent symptoms in their lifespan, which suggests that these subjects may not benefit from current disease‐modifying therapies for AD.
Increased Genetic Risk for ADHD Potentiates Cognitive Impairment and Brain Hypometabolism in Alzheimer’s Disease Patients
Authors: Leffa Douglas Teixeira , Povala Guilherme , Bellaver Bruna , Lussier Firoza Z , Ferrari‐Souza João Pedro , Ferreira Pamela C.L. , Zalzale Hussein , Aguzzoli Cristiano Schaffer , Rohden Francieli , Soares Carolina , Abbas Sarah , Tissot Cécile , Therriault Joseph , Lopez Oscar L. , Villemagne Victor L , Klunk William E , Cohen Annie , Zimmer Eduardo R. , Karikari Thomas K , Rosa‐Neto Pedro , Rohde Luis Augusto , Molina Brooke , Pascoal Tharick Ali 
Published: December 2023

AbstractBackgroundRecent epidemiological studies showed that patients with attention‐deficit/hyperactivity disorder (ADHD) are more likely to be diagnosed with Alzheimer’s Disease (AD). Additionally, increased genetic risk for ADHD, measured with ADHD polygenic risk scores (ADHD‐PRS), was associated with amyloid‐dependent cognitive decline in older adults. However, it is unclear whether higher genetic risk for ADHD is associated with worse cognitive function in patients with AD dementia.MethodWe used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to investigate the association between cognitive function (Preclinical Alzheimer Cognitive Composite [PACC], executive function, and memory) and ADHD‐PRS in subjects with AD dementia. Additionally, we tested whether ADHD‐PRS potentiated brain hypometabolism measured with [18F]FDG‐PET. Analyses were controlled by age, sex, years of study, and number of APOE ε4 alleles.ResultWe evaluated baseline data from 264 AD patients (114 women [43.2%], mean [SD] age of 75 [7.6] years). ADHD‐PRS was associated with decreased cognitive function (p‐value = .04, η2 = .01, Figure 1a), more specifically in executive function (p‐value = .04, η2 = .01, Figure 1c). Higher ADHD‐PRS was associated with brain hypometabolism in frontal, parietal, and temporal regions (Figure 2a,b). Brain hypometabolism correlated with worse cognitive function in the following regions: postcentral gyrus (p‐value = .01, η2 = .03), superior parietal gyrus (p‐value = .001, η2 = .07), precentral gyrus (p‐value = .004, η2 = .05), and fusiform gyrus (p‐value<.0001, η2 = .08, Figure 2c,d,e,f). Finally, decreased metabolism in these four regions mediated the effect of ADHD‐PRS on cognitive function (Figure 3).ConclusionFindings indicate that a higher genetic risk for ADHD is correlated with impaired cognitive function with small effect sizes. Moreover, the effects of the genetic risk of ADHD on cognitive function were mediated by hypometabolism in frontal, parietal, and temporal brain regions, which could point to a decrease resilience to AD pathology in individuals with ADHD. Clinically, our findings suggest that patients with comorbid ADHD and AD dementia have a more severe disease phenotype, with potential implications for prognosis and treatment.
Bearded capuchin monkey as a model for Alzheimer’s disease (AD) research
Authors: Rodriguez Roberta Diehl , Tavares Maria Clotilde Henriques , Brucki Sonia , Takada Leonel Tadao , Grinberg Lea T. , Otaduy Maria Concepción Gracía , Martin Maria Da Graça Morais , Costa Leite Claudia , Tomaz Carlos , Nitrini Ricardo 
Published: December 2023

AbstractBackgroundThe absence of a natural animal model is one of the main challenges to research in AD. AD‐type pathology has been described in chimpanzees and other primates’ brains. The bearded capuchin monkey (Sapajus libidinosus) is a New World primate that attracted attention mainly due to its skill in creating and using tools. We evaluated the brains of three captive capuchins (9, 29 and 33 years‐old) who died from natural causes at the Primate Center of University of Brasilia.MethodWhole brain was fixed in 4% buffered paraformaldehyde within 12 hours of death for three weeks. Structural 7T MRI was acquired in one case before brain slicing. Consecutive coronal sections from the fixed brain were embedded in paraffin, and 5um sections from paraffin blocks were used for staining and immunohistochemistry evaluation. All brain sections were stained with hematoxylin and eosin. Immunohistochemistry with β‐amyloid (4G8), phosphorylated tau (AT8), p62, TDP‐43, α‐synuclein (81A), 68 kDa neurofilament (2F11), GFAP and CD68 antibodies were performed in selected sections to analyze the following areas: frontal cortex, temporal cortex, parietal cortex, occipital cortex, anterior cingulate cortex, hippocampus, amygdala, basal ganglia, thalamus, mesencephalon, pons, medulla oblongata, and cerebellum.ResultMacroscopic evaluation of the brains showed considerable cortical gyrification. In addition, thick cortical ribbon was observed in the MRI. A complete neuropathological evaluation was available for two cases. Widespread β‐amyloid immunoreactivity was observed in the form of diffuse deposits, core‐space‐corona plaques, perivascular plaques, and amyloid angiopathy. A high frequency of classic neuritic plaques was observed. P‐tau antibody failed to label the dystrophic neurites. However, these lesions were revealed with p62 and neurofilament antibodies. Astrocyte hypertrophy surrounding plaques was observed without microglial activation. Very few hyperphosphorylated tau aggregates resembling neurofibrillary tangles and neuropil threads were found in the temporal and frontal cortex, and Lewy‐type and TDP‐43 pathology were not observed.ConclusionIn summary, we found β‐amyloid immunoreactivity, classic neuritic plaques surrounded by astrocyte hypertrophy, but only rare P‐tau aggregates. To our knowledge, this is the first evidence reporting brain AD‐like alterations in capuchin monkeys which suggest that this species can be considered an advantageous animal model for AD research.
Biomarkers of synaptic and neuronal dysfunction in relation to mild behavioral impairment: a study of dementia‐free older adults
Authors: Sharif Sergio Fernandez , Guan Dylan X. , Ghahremani Maryam , Leon Rebeca , Smith Eric E. , Ismail Zahinoor 
Published: December 2023

AbstractBackgroundMild behavioral impairment (MBI) represents a high‐risk state for incident cognitive decline and dementia, capturing later‐life emergent and persistent neuropsychiatric symptoms in five domains: 1) decreased motivation; 2) affective dysregulation 3) impulse dyscontrol; 4) social inappropriateness; and 5) psychosis. We examined cross‐sectional associations between MBI and cerebrospinal fluid levels of markers of synaptic/neuronal dysfunction including 1) alpha‐synuclein (α‐syn); 2) growth‐associated protein 43 (GAP‐43); 3) neurogranin (NGRN); 4) synaptosomal‐associated protein 25 (SNAP‐25); 5) visinin‐like protein 1 (VILIP‐1); and 6) chitinase‐3‐like protein 1 (YKL‐40). Longitudinally, we determined associations between these biomarkers and incident MBI or dementia.MethodAlzheimer’s Disease Neuroimaging Initiative participants with normal cognition and mild cognitive impairment were included (n = 853). MBI scores were derived from the Neuropsychiatric Inventory using a published algorithm. Participants were classified as MBI+ if MBI symptoms were present at ≥2 consecutive visits.Cross‐sectional associations between MBI total score and each log‐transformed biomarker were modelled using multivariable‐adjusted linear regression. Biomarkers with cross‐sectional associations meeting a pre‐defined p‐value threshold (p<0.1) were then incorporated as exposures into adjusted longitudinal Cox proportional hazard regression models (n = 111) of 1) MBI and 2) dementia as the outcomes, the latter of which also included interactions between MBI status and biomarker levels.ResultDemographics are summarized in Table 1. Cross‐sectionally, only MBI associations with VILIP‐1 (beta = 3.3%, 95%CI:+0.2% to +6.5%, p = 0.04) and SNAP‐25 (beta = 2.0%, 95%CI:‐0.4% to 6.3%, p = 0.09) met the pre‐defined p‐value for inclusion in Cox models. Longitudinally, higher VILIP‐1 levels were associated with a 3.02‐fold greater rate of incident MBI (95%CI:1.43‐6.40, p = 0.004) and a 3.83‐fold greater rate of incident dementia (95%CI:1.22‐12.03, p = 0.021). The relationship between VILIP‐1 and dementia did not depend on participants having MBI. MBI status predicted incident dementia with an HR = 4.75 (95%CI:2.36‐9.55, p<0.001) and HR = 4.06 (95%CI:2.01‐8.21, p<0.001) after adjusting for VILIP‐1.ConclusionElevated VILIP‐1 levels are associated with greater incidence of MBI and greater incidence of dementia, suggesting that synaptic dysfunction traditionally related to cognitive decline and dementia may also contribute to behavioral changes. Treatments aimed to mitigate MBI symptoms and dementia may explore VILIP‐1—a neuronal calcium‐sensor protein—as a therapeutic target, though more research is needed.
Sex modifies the relationship between cardiorespiratory fitness and insulin resistance
Authors: Edmunds Kyle J , McIntyre Clayton Connor , Breidenbach Bri M , Nelson Alexis R , Lose Sarah R , Bendlin Barbara B , Sager Mark A. , Asthana Sanjay , Johnson Sterling C , Okonkwo Ozioma 
Published: December 2023

AbstractBackgroundCardiorespiratory fitness (CRF) is a protective lifestyle factor against age‐related changes in insulin resistance in adults at‐risk for Alzheimer’s disease (AD); however, this association may differ between males and females. While sex‐dimorphic mechanisms of neurodegeneration and peripheral insulin have been proposed in aging models, it is still unclear whether sex differences exist in the influence of CRF. This study examines whether sex modifies the association between CRF and insulin resistance in a participant sample enriched with risk for AD.MethodThis study included n = 1,131 cognitively unimpaired, nondiabetic participants, where CRF was estimated using a validated equation that incorporates age, sex, BMI, resting heart rate, and self‐reported physical activity. The Homeostatic Model Assessment for Insulin Resistance (HOMA‐IR) quantified insulin resistance using measured plasma glucose levels in mg/dL and insulin in µIU/mL following a 12‐hour fast. Cross‐sectional linear regression models were assembled in a moderation framework to test the interaction between CRF and sex on HOMA‐IR scores using the IBM SPSS PROCESS Macro v3.4. All models controlled for age, education, Apolipoprotein E4 (APOE4) carriage, body mass index (BMI), and familial history of AD. Finally, sex‐stratified analyses were performed to test within‐group associations of CRF and HOMA‐IR.Result71.8% of participants had family history of AD and 38.8% were APOE4 carriers. Participants had a mean age of 64.5 ± 7 years and a mean of 16 ± 3 years of education. CRF was negatively associated with HOMA‐IR (β = ‐0.064, SE = 0.03, p = 0.04) and the interaction of CRF and sex was likewise significant (β = ‐0.114, SE = 0.03, p<.001). Stratified models showed that the magnitude of the association between CRF and HOMA‐IR was almost three times as strong among men than women (males: β = ‐0.178, SE = 0.03, p<.001; females: β = ‐0.06, SE = 0.03, p = 0.04).ConclusionAmong older adults at heightened risk for AD, CRF protects against insulin resistance; however, this association may be stronger in aging males than in females.
A multi‐stage feature selection method to improve classification of Super‐Ager and Cognitive Decliner using Structural brain MRI data – A UK Biobank study
Authors: Parvin Mohammadiarvejeh , Fili Mohammad , Hu Guiping , Willette Auriel A 
Published: December 2023

AbstractBackgroundCognitive aging is described as the age‐related declines in multiple cognitive abilities such as processing speed, memory, and executive function. However, old individuals with cognitive reserve are observed. Moreover, there are older adults aged more than 80 years, called Super‐Agers, who show cognitive abilities at least as good as middle‐aged adults, particularly in memory. Understanding the differences in brain structure between Super‐agers and Cognitive decliners can provide practical knowledge for middle‐aged adults to reserve the cognitive functions as they age and decrease Alzheimer’s Disease risk.MethodUsing the longitudinal cognitive tests of the UK Biobank, principal component analysis (PCA) was applied to combine the performance of the multiple cognitive domains to define the general cognitive ability (GCA) which was used to identify Super‐Ager and Cognitive Decline individuals. GCA 1 scores were extracted by processing speed, verbal and numeric reasoning, prospective memory, and visual declarative memory exams, and GCA 2 scores were extracted by executive function and processing speed exams. Random Forest (RF) classification models with a multi‐stage feature selection method were developed to distinguish Super‐Agers from Cognitive Decliners using the structural Magnetic Resonance (sMRI) features for two GCA 1 and 2 labels individually. Models’ performance and feature importance ranking were analyzed.ResultRF model achieved AUC of 73% with 54 selected sMRI predictors by GCA 1 labels, and age, education, area of total surface, area of pars orbitalis, mean intensity of thalamus, area of superior frontal were the top six features in classification. Also, RF models achieved AUC of 76% with 42 selected sMRI features by GCA 2 labels, and age, grey‐white contrast in pars triangularis, volume of CA3‐head, grey‐white contrast in pars opercularis, grey‐white contrast in frontal pole, and mean intensity of choroid plexus were the top six features in classification.Conclusionour results suggest that using PCA to combine various cognitive domains is an optimal method to analyze GCA in older adults and identify latent cognitive trajectory type. Furthermore, the multi‐stage feature selection model could find the most relevant sMRI features to classify Super‐Agers and Cognitive Decliners.
Cardiorespiratory fitness partially mediates the association between age and insulin resistance in a cohort enriched with risk for Alzheimer’s disease
Authors: Edmunds Kyle J , Breidenbach Bri M , McIntyre Clayton Connor , Lose Sarah R , Bendlin Barbara B , Sager Mark A. , Asthana Sanjay , Johnson Sterling C , Okonkwo Ozioma 
Published: December 2023

AbstractBackgroundAge is the cardinal risk factor for Alzheimer’s disease (AD), as well as adverse cardiovascular health and insulin resistance. In the context of promoting cerebrovascular health and resilience to AD, it remains unclear whether cardiorespiratory fitness (CRF)—an important lifestyle factor reflective of habitual exercise—explains age‐related associations in insulin signaling. Understanding how these factors intersect may be crucial for designing effective lifestyle interventions to protect normative brain function in aging. This study examines whether CRF mediates the relationship between age and insulin resistance in a sample enriched with risk for AD.MethodWe included n = 1,131 cognitively unimpaired, nondiabetic participants. CRF was estimated using a validated equation that incorporates age, sex, BMI, resting heart rate, and self‐reported physical activity. The Homeostatic Model Assessment for Insulin Resistance (HOMA‐IR) quantified insulin resistance using measured plasma glucose levels in mg/dL and insulin in µIU/mL following a 12‐hour fast. Cross‐sectional linear regression models were assembled in a mediation framework to test the mechanistic influence of CRF using the IBM SPSS PROCESS Macro v3.4, where indirect effects were estimated using bootstrapping. All models controlled for age, education, Apolipoprotein E4 (APOE4) carriage, body mass index (BMI), and familial history of AD.Result71.8% of participants had family history of AD and 38.8% were APOE4 carriers. Participants had a mean age of 64.5 ± 7 years and a mean of 16 ± 3 years of education. Age was significantly associated with estimated CRF [β = ‐0.346; p<0.001] and HOMA‐IR [β = ‐0.036; p<0.01]; CRF was likewise negatively correlated with HOMA‐IR [β = ‐0.106; p<0.001]. Bootstrapping indicated that CRF was a significant partial mediator of the association between age and HOMA‐IR [β = 0.37; 95% CI: 0.19, 0.55].ConclusionAge exerts its deleterious influence on peripheral insulin resistance through the degradation of cardiorespiratory fitness among adults at risk for AD.
Cerebral microhemorrhage associations in UK immigrants from the Middle East and North Africa (MENA)
Authors: Haddad Elizabeth , Sheikh‐Bahaei Nasim , Javid Shayan , Jahanshad Neda 
Published: December 2023

AbstractBackgroundPeople from the Middle East and North Africa (MENA) are highly underrepresented in health studies, yet, they are forecasted to contribute the most to increasing projections of dementia over the next 30 years (Nichols, 2022). Cerebral microhemorrhages, or microbleeds (CMBs) in the aging brain have been linked to small vessel disease and neurodegeneration and may provide a proxy for intervention studies to identify those at higher risk for ADRD (Charidimou, 2011). CMBs are related to hemorrhagic amyloid‐related imaging abnormalities (ARIA‐H) reported as adverse events in recent Alzheimer’s clinical trials of amyloid clearing medications (Sperling, 2011). Identifying those at elevated risk for ARIA‐H can help refine inclusion criteria for clinical trials and mitigate risk of complications from these medications. CMBs may be detected by MRI derived susceptibility weighted images (SWI) (Haacke, 2004). We’ve previously reported higher prevalences of metabolic and cardiovascular disorders in MENA compared to other immigrant populations in the UK (Jahanshad, 2022). Using a subset of these individuals with SWI (Miller, 2016), we investigated the effect of these diseases and lifestyle on the presence of CMBs detected on SWI.Method185 MENA participants with SWI were included. We used MARS criteria (Gregoire, 2009) to identify CMBs on SWI and validated our findings using other sequences to exclude CMB ‘mimics’ (Figure 1). The number and position of CMBs were reported as well as their classification including ‘definite’, ‘possible’ and ‘total’. The effects of disease and lifestyle were investigated using association rule learning, and Chi‐squared/Fisher’s exact tests were used on the most prominent associations.Result10 subjects had at least one definite CMB and 10 more had at least one possible CMB (Table 1). Combinations of male sex, diabetes, obesity, and high waist‐to‐hip ratio were found to have 100% likelihood for having a CMB. The presence of definite CMBs was associated with diabetes (p = 0.017) and overweight BMI (p = 0.017) (Figure 2).ConclusionCMBs were associated with male sex, diabetes, and abnormally high anthropometric measures in MENA populations. Future work will test a larger sample and continue to tease apart CMB associations with health markers in those from MENA countries.