bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brain glucose metabolism changes acutely following exercise and tracks with the systemic lactate response
Authors: Green Zachary D. , John Casey S. , Blankenship Anneka , Kueck Paul J , Kemna Riley E , Johnson Chelsea N , Mahnken Jonathan D , Yoksh Lauren , Burns Jeffrey M , Donald Joseph S. , Vidoni Eric D , Morris Jill K 
Published: January 2025

AbstractBackgroundAerobic exercise may positively affect brain health, although relationships with cognitive change are mixed. This likely is due to individual differences in the systemic physiological response to exercise. However, the acute effects of exercise on brain metabolism and biomarker responses are not well characterized in older adults or cognitively impaired individuals.MethodThe Acute Exercise Response on Brain Imaging and Cognition (AEROBIC) study is a randomized, controlled trial (NCT04299308). We enrolled older adults (60+years) who were cognitively healthy (n = 30) or cognitively impaired (n = 30) based on a clinical exam (telephone CDR). Study visits included a cardiorespiratory fitness test, Fluorodeoxyglucose [18F] PET (FDG‐PET) scans with timecourse blood draws during both rest and exercise, and resting MRI. Participants were randomized to both intensity (moderate; 45‐55% heart rate reserve (HRR) or higher (65‐75% HRR)) and PET visit order. Lactate and various exercise‐related biomarkers were measured. Each session concluded with cognitive testing (NIH Toolbox). Change in whole‐grey matter cerebral glucose metabolism from rest to exercise was registered as the primary outcome. We used general linear modeling to test for a primary effect of Condition (exercise vs. rest), as well as the effects of intensity and cognitive diagnosis, on the change in FDG‐PET SUVR and lactate AUC.ResultFDG‐PET SUVR differed significantly between exercise (1.045 ± .082) and rest (.985 ± .077) across the entire cohort (Diff = ‐.060, t(58) = 13.8, p < .001). The effect of exercise (F(1,54) = 193.086, p < .001) was not dependent on diagnosis or intensity. Exercise increased Lactate AUC (F(1,56) = 161.988, p < .001), an effect stronger in the Higher intensity (MD = 97.0±50.8) than in the Moderate intensity (MD = 40.3±27.5; t = ‐5.252, p<0.001) group. Change between exercise conditions for lactate AUC and FDG‐PET SUVR correlated (R2 = 0.179, p<.001).ConclusionAcute exercise decreases brain glucose metabolism in both cognitively healthy and impaired older adults. This effect tracks with the systemic lactate response. This supports the hypothesis that increased lactate may spare glucose and be a key brain fuel during exercise. Additional work to directly measure brain lactate metabolism following exercise and understand the role of central and peripheral lactate metabolism is warranted.
A single nucleotide polymorphism from a differentially‐expressed gene shared across four neurodegenerative diseases increases tau accumulation independently of amyloid
Authors: Ramos Vanessa G. , Carello‐Collar Giovanna , Schlickmann Thomas Hugentobler , Siebert Marina , Cristino Alexandre Santos , Bastiani Marco De , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundNeurodegenerative diseases (NDs), including Alzheimer's disease (AD), Huntington's disease (HD), Multiple Sclerosis (MS), and Parkinson's disease (PD) are characterized by the accumulation of misfolded proteins and progressive loss of neurons. However, whether a neurodegeneration transcriptomic signature exists remains uncertain. Thus, we aimed to explore differentially expressed genes (DEGs) in common to AD, HD, MS, and PD. We also seek to evaluate the effect of single nucleotide polymorphisms (SNPs) derived from the NDs‐shared DEGs on AD pathophysiology.MethodsWe obtained RNA‐sequencing and microarray datasets of vulnerable brain regions of AD, HD, MS, and PD individuals from the Gene Expression Omnibus. Differential gene expression analysis (adjusted p‐value < 0.05) was conducted to identify DEGs in common among these four NDs. Then, we examined the impact of shared DEG‐related SNPs on amyloid and tau burden in AD through a linear regression model adjusted for the covariates of age, sex, and ApoEε4 status. We obtained DEG‐related SNPs and amyloid‐ and tau‐PET data from the Alzheimer's Disease Neuroimaging Initiative (ADNI).ResultsWe identified 467 DEGs in common among AD, HD, MS, and PD vulnerable brain regions (Figure 1, p‐value < 0.05). From these DEGs, 15,574 SNPs were available in ADNI. Linear regression analysis revealed that IQGAP2 rs79679327 carriers had higher tau accumulation independently of amyloid burden (Figure 2, p‐value = 0.001; carriers: n = 21, mean age ± standard deviation (SD) = 72.76 ± 4.54; non‐carriers: n = 176, mean age ± SD = 71.64 ± 6.85).ConclusionHere, we show transcriptional similarities across four NDs. In AD, individuals carrying the IQGAP2 rs79679327 variant exhibited greater tau accumulation, regardless of amyloid. Our findings may provide insights into neurodegenerative traits, through a common signature of neurodegeneration.
Structural desegregation of salience network is associated with executive functioning deficits in behavioral variant frontotemporal dementia
Authors: Matyi Melanie A , Radhakrishnan Hamsi , Phillips Jeffrey S , Cook Philip A. , Rhodes Emma , Gee James C. , Irwin David J , McMillan Corey T , Massimo Lauren 
Published: January 2025

AbstractBackgroundThe human brain is organized in dense and distinct intrinsic networks that are topographically arranged and mediate particular cognitive functions. The characteristic of intrinsic network organization that supports this functional specialization of cognitive domains is known as modular segregation. Neurodegeneration is associated with changes in brain network organization that contribute to cognitive decline among healthy older adults but network segregation has rarely been studied in behavioral variant frontotemporal dementia (bvFTD). Examining segregation may provide insights into network organization and its contribution to cognition in bvFTD. We hypothesize that desegregation of structural networks will differ between bvFTD and healthy controls (HC) and will be associated with deficits in high‐executive demand cognitive tasks in bvFTD patients.Methods86 bvFTD and 37 HC (see Table 1) underwent diffusion MRI. Patients also completed tests of letter‐guided fluency, category‐naming fluency, and the Boston Naming Test (BNT). Structural connectivity was derived from deterministic tracking among 100 cortical regions mapped to 7 intrinsic networks, defined by the Schaefer atlas, using the DSI‐Studio generalized q‐sampling imaging pipeline as implemented in QSIPrep. Network segregation was characterized by high within‐network connectivity but low between‐network connectivity. To identify patterns of desegregation in structural networks, one‐way ANOVAs were conducted between bvFTD and HC groups for each network, controlling for age and motion. Linear regression was then performed to assess whether desegregation was associated with executive performance, controlling for disease duration and education.ResultsDesegregation of the salience network was observed in bvFTD, relative to HC (see Figure 1) and was associated with deficits in tasks with high executive demand (letter‐guided and category‐naming fluency), but not with performance on the BNT, a task with lower executive demand (see Figure 2).ConclusionsResults indicate that structural desegregation of salience network is characteristic of bvFTD, reflecting a reduced capacity for specialized processing. Salience network desegregation was also uniquely associated with performance on cognitive tasks requiring high demand on executive resources. Overall, findings underscore the importance of salience network in bvFTD pathology. Critically, results demonstrate the executive consequences of network desegregation.
Establish Stronger Correlation between Surrogate Endpoint and Clinical Endpoint Using All Post‐baseline Data
Authors: Li Yan , Wang Guoqiao 
Published: January 2025

AbstractBackgroundA traditional method for validating a surrogate endpoint typically involves assessing the correlation between changes in biomarkers and changes in clinical endpoints using Pearson’s and/or Spearman’s correlation. However, this approach may not provide an accurate representation of the true correlation due to several reasons: (i) it only considers the change from baseline to the last visit and does not use all post‐baseline longitudinal data; (ii) the raw change has large variability; (iii) it does remove the within‐subject variability. The objective of this presentation is to propose two alternative approaches that overcome these limitations and allow for a more accurate estimation of the true correlation using all available longitudinal data.MethodWe propose two models that have the capability to eliminate within‐subject variability and utilize all available post‐baseline longitudinal data for estimating the correlation: (i) bivariate linear mixed effects (bivariate‐LME) model utilizing time as a continuous variable, and (ii) bivariate MMRM with random effects (bivariate‐MMRM‐RE) utilizing time as a categorical variable. Through simulations that mimicking treatments with disease modifying effects, we will compare the estimated correlations using these two models to the Pearson’s and/or Spearman’s correlations.ResultOur preliminary simulations showed that the Pearson’s and/or Spearman’s correlation tends to significantly underestimate the true correlation. And the magnitude of underestimation increases with shorter trial durations. On the other hand, correlations estimated from both the bivariate‐LME model and bivariate‐MMRM‐RE model demonstrate higher accuracy compared to the true correlation estimation, and they are also less influenced by the trial duration.ConclusionThe Pearson’s and/or Spearman’s correlations estimated from clinical trial data are usually small (eg, 0.19 between the change in amyloid PET and CDR SB in EMERGE). Our simulations suggest that the Pearson’s or Spearman’s correlation is smaller than the true correlation. Therefore, it is advisable to estimate the true correlation using either the bivariate‐LME model or the bivariate‐MMRM‐RE model. These models provide more accurate estimations of the true correlation compared to the traditional Pearson’s and/or Spearman’s correlation.
The landscape of dementia research in Brazil (2010‐2021): A Scopus‐based bibliometric study
Authors: Ramos Ari Alex , Bertola Laiss , da Mata Fabiana A F , Miguel Andrew Christopher , Júnior Haliton Alves de Oliveira , Ferri Cleusa P 
Published: January 2025

AbstractBackgroundIn the last two decades, several studies have sought to investigate the trajectory of scholarly publications on dementia. Yet, there has been limited attention to contributions from Latin America. This bibliometric review aimed to partially address this gap by providing a comprehensive overview of the literature output on dementia in Brazil. Moreover, we were particularly interested in categorizing each included publication according to the research areas in dementia recently defined by the World Health Organization.MethodWe conducted a Scopus‐based literature search for publications indexed between 2010 and 2021 and developed syntaxes into R software for data analysis.ResultAmong the 5,534 documents found in Scopus, 2,528 met the inclusion criteria. The annual growth rate of publications on dementia (9.9%, SD = 15.5) closely paralleled that of general health‐related literature (6.7%, SD = 4.9), with no statistically significant differences between the two rates. Over 65% of the publications were categorized into the areas of dementia diagnosis (33.4%) and disease mechanisms, origins, and models (32.7%), followed by dementia care (14.9%), drug development (7.2%), risk reduction (6.5%), and epidemiology (4%). There were notably low percentages of publications related to clinical trials (1%) and economic cost (0.3%). Based on the first affiliation of Brazil‐affiliated authors with leading authorship roles (first, second, second‐to‐last, and/or last authors), approximately 90% of the analyzed affiliations stemmed from the Southeast (68.4%) and South (20.9%). However, the State of São Paulo accounted for 41.1%, contributing to 60.1% of the Southeast. Interestingly, 55% of authors holding leading authorship roles were women. Furthermore, first and second authorships were predominantly held by female researchers, whereas male researchers occupied most of the second‐to‐last and last authorships. Overall, 71.7% of the included reports were published in 346 foreign journals and 28.3% in 43 Brazilian journals. The National Council for Scientific and Technological Development (CNPq, 19.5%) and the Coordination for the Improvement of Higher Education Personnel (CAPES, 11.8%) were the leading research funding agencies acknowledged in the analyzed publications.ConclusionThere is a pressing need for more studies across all Brazilian regions and all areas of dementia research, especially in epidemiology and economic cost.
24‐hour activity cycle movement behaviours and brain volume in people with mild cognitive impairment: A compositional and isotemporal substitution analysis
Authors: Balbim Guilherme Moraes , Silva Nárlon Cássio Boa Sorte , Falck Ryan S , Liu‐Ambrose Teresa 
Published: January 2025

AbstractBackgroundPeople with mild cognitive impairment are at greater risk of Alzheimer’s disease. Physical activity (PA), sedentary behaviour, and sleep are movement behaviours constituting the 24‐hour activity cycle (24‐HAC) and are interactively associated with cognitive and brain health. However, the relationship between 24‐HAC compositions (i.e., time in one behaviour relative to remaining) and brain volume in this population remains underexplored. We aimed to investigate the associations between 24‐HAC compositions and time reallocation of 24‐HAC movement behaviours with brain volume.MethodA cross‐sectional study in 110 community‐dwelling adults (55+ years) with mild cognitive impairment (Montreal Cognitive Assessment <26/30). MotionWatch8© assessed 24‐HAC movement behaviours (5‐7 days). Compositional data analysis determined 24‐HAC compositions (four isometric log‐ratio pivot coordinates). FreeSurfer quantified gray matter volume using T1‐weighted magnetic resonance imaging. Linear regressions adjusted for age, sex, intracranial volume, and education determined 24‐HAC compositions and brain volume associations. Compositional isotemporal substitution analysis estimated the difference in brain volume associated with reallocating time between pairs of 24‐HAC movement behaviours. The Benjamini‐Hochberg false‐discovery rate (FDR) adjusted p‐values for multiple comparisons.ResultHigher moderate‐to‐vigorous PA composition was associated with greater cortical volume in the inferior temporal gyrus TE2a region (ß = 0.30, 95% CI = 0.15; 0.44, FDR‐adjusted‐p = 0.030). Higher light PA composition was associated with lower cortical volume in the TE2a region (ß = ‐0.45, 95% CI = ‐0.65; ‐0.24, FDR‐adjusted‐p = 0.015). Sedentary behaviour and sleep were not associated with brain volume (FDR‐adjusted‐p>0.05). Reallocating 30 minutes from sedentary behaviour to moderate‐to‐vigorous PA was associated with 2.1% greater volume in the TE2a region (ß = 0.06, 95% CI = 0.02; 0.10, p<0.001). Reallocating 30 minutes from moderate‐to‐vigorous PA to sedentary behaviour was associated with 2.8% lower volume in the TE2a region (ß = ‐0.08, 95% CI = ‐0.14; ‐0.02, p<0.001).ConclusionGreater light PA composition may happen at the expense of lower moderate‐to‐vigorous PA composition, which could explain its associations with lower cortical volume. Greater moderate‐to‐vigorous PA composition and reallocating time from sedentary behaviour to moderate‐to‐vigorous PA may counteract cortical atrophy in an Alzheimer’s disease signature region in people with mild cognitive impairment.
Population Attributable Fractions for Risk Factors for Dementia in Latin America
Authors: Paradela Regina Silva , Calandri Ismael Luis , Pozo Natalia , Garat Emanuel , Delgado Carolina , Crivelli Lucia , Yaffe Kristine , Ferri Cleusa P , Mukadam Naaheed , Livingston Gill , Suemoto Claudia Kimie 
Published: January 2025

AbstractBackgroundApproximately 40% of global dementia cases are associated with 12 modifiable risk factors (less education, hearing loss, hypertension, obesity, smoking, depression, social isolation, physical inactivity, diabetes, alcohol excess, air pollution, and traumatic brain injury). However, the number of people with these risk factors differs between populations. Latin American countries differ in socioeconomic and geographic aspects and, therefore, risk factors prevalence. Our goal was to determine the population‐attributable fraction (PAF) of these risk factors (combined and individually) for dementia by analyzing population‐based samples from seven countries in Latin America (LA).MethodWe used data from Argentinian, Brazilian, Bolivian, Chilean, Honduran, Mexican, and Peruvian cross‐sectional, nationally representative surveys with harmonized measurements of the 12 modifiable risk factors for dementia. Data were collected between 2015 and 2021, and the survey sample size varied from 5,995 to 107,907 participants aged 18 years or older across the seven countries. We calculated the risk factor prevalence and their communalities in each country and used these with relative risks for dementia from previous meta‐analyses to calculate the PAFs. Pooled PAFs for LA were then obtained using random effect meta‐analyses.ResultThe overall proportion of dementia cases attributed to 12 modifiable risk factors varied across LA countries (62% in Chile, 60% in Argentina, 56% in Bolivia, 56% in Mexico, 54% in Honduras, 48% in Brazil, and 45% in Peru), with an overall PAF of 54% for LA (95% CI 48.8‐59.6). Obesity (weighted PAF = 7%), physical inactivity (weighted PAF = 6%), and depression (weighted PAF = 5%) had the highest PAFs in LA.ConclusionThere is potential for prevention of a higher proportion of dementia in LA than worldwide. Obesity, physical inactivity, and depression are the major contributors to dementia variance across the seven LA countries. These findings have implications for dementia prevention strategies in LA.
Determinants of loneliness and depressive symptomatology among LGBTQ older adults living with cognitive impairment
Authors: Kim Hyun‐Jun , Fredriksen‐Goldsen Karen I , Jung Hailey H. , Lee Chaejeong 
Published: January 2025

AbstractBackgroundLoneliness and depression among older adults are linked to a higher likelihood of chronic diseases, deterioration of physical function, and compromised quality of life. LGBTQ older adults are known to experience social isolation and mental distress at higher rates than their heterosexual counterparts, and those with cognitive impairment may be particularly susceptible to loneliness and depression. However, there is limited knowledge regarding the risk and protective factors for loneliness and depression among LGBTQ older adults living with cognitive impairment. This study fills this critical research gap and provides insights to improve the well‐being of this historically marginalized and underserved population.MethodA sub‐sample (N = 160) of the Aging with Pride: National Health, Aging, and Sexuality/Gender Study (NHAS), the first longitudinal study of LGBTQ adults aged 50 and older in the U.S., was used. Those who were identified as experiencing cognitive impairment based on their Montreal Cognitive Assessment (MOCA) scores were included in this study. The MOCA scores ranged from 14 to 25 with a mean score of 22.1 (SD = 2.7). Mixed models were tested to identify factors predicting the overall levels and slopes of loneliness and depressive symptomatology over 6 years (2014 – 2020).ResultThe mean age was 68 (range: 50 – 97) with 69% men, 44% people of color, 55% with income below 200% federal poverty guideline, and 22% with high school or less education. Half reported feeling lonely, and about 30% had clinical‐level depressive symptoms. After controlling for background characteristics, loneliness and depressive symptomatology were positively associated with everyday discrimination, sub‐optimal sleep, and limited social resources. Loneliness was also positively associated with being single and limited outdoor activity, and depressive symptomatology with identity stigma and malnutrition. Loneliness increased over time if being single.ConclusionFindings identify modifiable factors that may provide protection against loneliness and depressive symptomatology. Individuals living with cognitive impairment and no care partner had loneliness increase over time, which is of particular concern. This study provides evidence‐based information for the development of tailored interventions, addressing LGBTQ‐specific needs as well as enhancing independence in daily living and overall quality of life.
Neuroimaging Markers of Microstructural Neurodegeneration are More Sensitive to Cognitive Dysfunction than Hippocampal Volume in Early Alzheimer’s Disease: A Mixed‐Longitudinal Study
Authors: Moody Jason F , Jonaitis Erin M. , Langhough Rebecca E. , Dean Douglas C , Alexander Andrew L , Johnson Sterling C. , Bendlin Barbara B. 
Published: January 2025

AbstractBackgroundWhile magnetic resonance imaging (MRI) markers of neurodegeneration are nonspecific to Alzheimer’s disease (AD) pathology, they have been correlated with cognitive dysfunction, and therefore, provide important information pertaining to disease staging. Neurodegeneration in AD is commonly assessed with macrostructural measures of brain atrophy, such as hippocampal volume. However, recent investigations have shown that markers of neural microstructure derived from diffusion MRI (DWI) may provide supplementary insight into the progression of AD pathophysiology. Furthermore, DWI measures of neurite density index (NDI), isotropic volume fraction (ISO), return to origin probability (RTOP), and mean squared displacement (MSD) have recently been associated with cerebrospinal fluid markers of senile plaques, neurofibrillary tangles, and AD‐related neurodegeneration.In this study, we used linear mixed‐effects (LME) modeling to compare the utility of different MRI markers for predicting performance on a three‐test Preclinical Alzheimer’s Cognitive Composite (PACC3) in 268 late‐middle‐aged participants.Methods268 participants from the Wisconsin Registry for Alzheimer’s Prevention and the Wisconsin Alzheimer’s Disease Research Center (216 unimpaired, 37 MCI, 15 AD) were imaged between 1 and 2 times with T1‐weighted MRI and multi‐shell DWI (Table 1). For each scan, hippocampal volume was estimated and average NDI, ISO, RTOP, and MSD values were extracted from the hippocampus and anterior parahippocampal gyrus. PACC3 scores were calculated from comprehensive neuropsychological testing within 6 months of imaging. Neuroimaging metrics were used as predictors in separate LME models of the following form:PACC3 = b0 + b1*(metric) + b2 *(age) + b3*(sex) + b4*(metric*clinical status) + b5*(years of education) + uiResultsDWI metrics consistently outperformed hippocampal volume in predicting PACC3 scores across both brain regions (Table 2). Anterior parahippocampal MSD exhibited the lowest AIC/BIC values, while hippocampal NDI had the strongest association with PACC3 scores among unimpaired participants. Meanwhile, hippocampal volume had the largest AIC/BIC values and the weakest correlation with PACC3 scores (Table 2, Figure 1).ConclusionOur study provides evidence that neuroimaging markers of brain microstructure may be particularly sensitive to subtle alterations predictive of cognitive performance, especially early in AD. Future work will translate these analyses to larger cohorts and incorporate fluid markers of amyloid and tau.