bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fatigue in vascular cognitive impairment no dementia
Authors: Ciopleias Bogdan , Diaconu Stefania , Irincu Laura , Despa Irina , Opritoiu Bianca , Cusnir Malina , Ungureanu Larisa , Kakucs Cristian , Falup‐Pecurariu Cristian 
Published: December 2023

AbstractBackgroundpatients with vascular cognitive impairment no dementia (VCI‐ND) may have different complains like sleep disturbancies, fatigue, pain. Fatigue is one of the most common symptoms of these patients. In advanced stages, fatigue is difficult to describe by the patients. Aim of the study: to assess the frequency and risk factors for fatigue in patients with VCI‐ND.Methodthis is a case‐control study, which involved 23 people with VCI‐ND and 23 sex and aged matched controls (with no dementia). A comprehensive neurological assessment in both groups were performed; adittionally we used Hamilton Anxiety and Depression Scale, Epworth Sleepiness Scale, McGill Pain Questionnaire, Fatigue Severity Scale (FSS)Resultfatigue was described by 7 patients (30.43%) in the study group compared with 2 patients (8.69%) in controls (p<0.05). In the study group, when patients with fatigue were compared with those with no fatigue, the first group had higher Hamilton Anxiety and Depression Rating Scale score and higher Epworth Sleepiness Scale score.Conclusionthis study suggest that fatigue is quite common among people with vascular cognitive impairment no dementia. Anxiety, depression, excessive daytime sleepiness were independently associated with fatigue.
An exploration of the relationship between financial hardship and cognitive functioning in later life
Authors: Marshall Gillian L. , Stansbury Kim 
Published: December 2023

AbstractBackgroundThere is a connection between stress and negative health outcomes including cognitive impairment. Few studies have examined the relationship between perceived financial hardship as a secondary stressor and cognitive function. This study aimed to test four indicators of perceived financial hardship and the impact on cognitive function among older adults.MethodsUsing data from four waves of the Health and Retirement Study of persons 65 years and older, we analyzed (N = 6612) across waves 1 and 2 using generalized linear regressions. There were four financial hardship variables (difficulty paying bills, food insecurity, taking less medication due to cost and ongoing financial strain). Cognitive status was conceptualized as a composite variable of episodic memory and mental status.ResultsResults suggests that all four financial hardships were associated with lower mental status scores with food insecurity having the strongest association of the four indicators.ConclusionThese findings highlight the negative effects of stress in later life. Even secondary stressors such as financial hardships do in fact tax the mental status of older persons. There are higher risks for cognitive impairments in older adults with financial hardships than those without financial hardships This study underlines the importance of interventions to reduce stress while also creating greater access to food and medications specifically.
Association between glial and synaptic fluid biomarkers and brain [18F]FDG‐PET signal
Authors: Machado Luiza Santos , da Rocha Andreia Silva , Antônio De Bastiani Marco , Bellaver Bruna , Soares Carolina , Lazzarotto Gabriela , Vidor Pedro , Schlickmann Thomas , Rahmouni Nesrine , Siebert Marina , Ferreira Pamela C.L. , Pascoal Tharick A. , Souza Diogo O. , Rosa‐Neto Pedro , Benedet Andrea Lessa , Blennow Kaj , Zetterberg Henrik , Ashton Nicholas J. , Zimmer Eduardo R. 
Published: December 2023

AbstractBackgroundBeyond the hypometabolic signature, indexed by [18F]FDG‐PET imaging, seen in the brain of Alzheimer’s disease (AD) patients, a transient brain glucose hypermetabolism has been recently identified in the early stages of AD. The cellular source of this dual metabolic response remains controversial, with glial cells gaining a lot of attention. In light of this, whether glial and synaptic fluid biomarkers are associated with [18F]FDG‐PET signal in the early stages of AD remains debatable. Thus, we evaluated the association of astrocyte, microglial and synaptic fluid biomarkers with [18F]FDG‐PET signal in an AD rat model.Method[18F]FDG‐PET imaging was conducted in ten‐month‐old (early amyloid stage) APP/PS1 (TgF344‐AD, n = 8‐17) and wild‐type (WT, n = 8‐15) rats. Glial (GFAP and sTREM2), synaptic (neurogranin), and amyloid biomarkers (Aβ1‐40 and Aβ1‐42) were quantified in the cerebrospinal fluid (CSF) and plasma through a multiplex immunoassay. T‐statistical maps of brain [18F]FDG‐PET and those fluid biomarkers were conducted at the voxel level using RMINC. Differences were considered statistically significant at p<0.05 (t>2).ResultA large hypermetabolic cluster was identified in ten‐month‐old TgF344‐AD (Fig. 1AB, local maxima, t(13) = 4.28). We found positive correlations between CSF TREM2 and brain [18F]FDG‐PET signal (Fig. 2AC, local maxima, t(13) = 4.12). In addition, we identified a positive correlation between plasma GFAP and brain [18F]FDG‐PET signal (Fig. 2BC, local maxima, t(13) = 10.62). Plasma TREM2, CSF GFAP, and plasma neurogranin did not associate with brain glucose metabolism.ConclusionOur findings suggest that CSF TREM2 and plasma GFAP are associated with brain metabolism before amyloid load reaches a plateau. Stronger association of plasma GFAP, rather than CSF GFAP, with brain pathology corroborates cross‐sectional human studies. One could argue that [18F]FDG‐PET hypermetabolism identified is likely a response to astrocyte and microglial changes.
Development of a selective estrogen β‐receptor phytoestrogen formulation – PhytoSERM – for the reduction of Alzheimer’s risk and relief of menopausal symptoms in women: a phase 2 randomized clinical trial framework
Authors: Hernandez Gerson D , Lopez Claudia M , Raikes Adam C. , Matthews Dawn C , Mosconi Lisa , Brinton Roberta Diaz 
Published: December 2023

AbstractBackgroundThe greatest risk factors for Alzheimer’s disease (AD) are age, APOɛ4 allele and female sex. The estimated lifetime risk for AD is 19.5% for women compared to 10.3% in men. Accumulating evidence points to life‐time estrogen exposure as a protective factor against cognitive decline and AD in women, and to the menopause transition as a trigger for an existing AD predisposition. Estrogen replacement therapy (ERT) is effective for sustaining neurological health, but fear of breast cancer is the principal reason menopausal women reject it. Instead, women utilize over the counter products labeled as natural and considered to be safer. Thus, to attain brain protection and address breast protection we developed a rationally designed combination of select ERβ‐selective phytoestrogens that promote brain health to reduce AD risk without increasing breast cell proliferation.MethodA total of 100 participants, 50 per treatment arm, will be enrolled. Eligible participants are woman, 45‐60 years, peri or post‐menopausal (last menstrual period completed ≥ 60 days and ≤ 4 years), MoCA≥22, and experiencing ≥7 hot flashes per day. Participants will be randomized to 50 mg of PhytoSERM or placebo (orally, once‐per‐day) for a 24‐week period. FDG‐PET scans will be conducted at baseline and 24 weeks. Cognitive measures and clinical ratings will be assessed. Hot flashes will be measured both subjectively with a diary and objectively with a digital wristband measuring electrodermal activity.ResultPrimary endpoint is change from baseline to 24 weeks in regional brain glucose metabolism standardized uptake value ratio (SUVR). Secondary outcome measures include cognitive test battery scores, hot flash score and clinical ratings scores. Exploratory measures will include MRI brain volumes, fractional anisotropy, quantitative anisotropy, functional connectivity, and cerebral blood perfusion.ConclusionHerein we present a phase 2 proof‐of‐concept framework to assess the efficacy of PhytoSERM as a potential non‐pharmacologic therapeutic to improve cognitive health and reduce menopausal symptoms. Results from this study will validate previous findings that indicate that PhytoSERM is a safe alternative to hormone therapy and has the potential to sustain neurological health during the menopausal transition.
Association of MRI markers of vascular injury and neurodegeneration and cognitive decline in diverse cohorts: Findings from KHANDLE and STAR
Authors: Lor Yi , Decarli Charles , Peterson Rachel , George Kristen M , Gilsanz Paola , Mungas Dan M. , Mayeda Elizabeth Rose , Barnes Lisa L. , Whitmer Rachel A. 
Published: December 2023

AbstractBackgroundMRI biomarkers of vascular injury and neurodegeneration are associated with cognitive decline, but relatively little is known about cognitive change in diverse populations. Our objective is to examine associations of hippocampal volume and white matter integrity on cognitive change over 3 years.MethodKHANDLE (age 65+) and STAR (age 50+) are harmonized cohorts of racially/ethnically diverse long‐term members of Kaiser Permanente Northern California. A random sub‐sample of participants received neuroimaging with 3T MRI to measure regional brain volumes and white matter integrity. Hippocampal volume (cm3), log white matter hyperintensities (log‐WMH) (cm3), free water (FW) (cm3), and fractional anisotropy (FA) MRI measures were normalized on intracranial volume and age at scan. Cognitive decline was assessed across three waves using the Spanish English Neuropsychological Assessment Scale measuring executive function (EF) and verbal episodic memory (VEM). Linear mixed models allowing for random intercept and slope estimated the associations of MRI metrics and cognition adjusting for baseline age, education, gender/sex, interview mode (in‐person vs phone), and interactions of these covariates with time from baseline, to adjust for effects of covariates on both baseline cognition and cognitive change.ResultAmong 592 participants with neuroimaging, 59% were women, 47% were college educated, and 52% were Black adults (Table 1). Hippocampal volume was positively associated with baseline VEM (β = 0.268; CI = 0.153, 0.383) and EF change (β = 0.051; CI = 0.009, 0.094) (Table 2, Plot 1). FW was negatively associated with baseline EF (β = ‐6.561; CI = ‐10.758, ‐2.364), baseline VEM (β = ‐5.557; CI = ‐10.03, ‐1.084) and EF decline (β = ‐1.667; CI = ‐3.268, ‐0.066). FA was positively associated with baseline EF (β = 6.222; CI = 3.217, 9.228) and baseline VEM (β = 6.944; CI = 3.768, 10.119). Log‐WMH was negatively associated with baseline EF (β = ‐0.068; CI = ‐0.116, ‐0.020) and VEM (β = ‐0.082; CI = ‐0.132, ‐0.032).ConclusionAll MRI markers were associated with baseline cognition, but only hippocampal volume and FW were associated with cognitive change. MRI measures of neurodegeneration and white matter integrity may be predictive of cognition and short‐term decline in diverse groups of older adults. Future analyses will examine associations with cognitive impairment.
Neighborhood problems and sleep difficulties predict subjective cognitive decline in Black American men living in urban areas
Authors: Egwuonwu Joshua , Esiaka Darlingtina 
Published: December 2023

AbstractBackgroundThe impact of the residential neighborhood on health and aging is being increasingly recognized in medical and health sciences. Specifically, research suggests that the neighborhood where people live can be a risk or protective factor for various health outcomes, including brain health. Similar to the impact of neighborhood on health and aging, sleep has been linked to subjective cognitive decline (SCD) in older adults, which may signal a cognitive trajectory to Alzheimer’s disease and related dementia (ADRD). This study aims to evaluate whether neighborhood problems and sleep difficulties predict subjective cognitive decline in Black men living in urban areas and, thus, may be related to elevated risks for ADRD.MethodBlack American men (N = 117), age 40 – 70 years, were recruited through a targeted advert on Amazon Mechanical Turk (MTURK) over a 3‐week period. The participants responded to a survey assessing neighborhood problems, bodily symptoms, length of residence, sleep difficulties, self‐rated health, sociodemographic characteristics, and subjective cognitive decline.ResultWe performed hierarchical regression. In Model 1, only education was a significant predictor of SCD (F (3,113) = 8.52, p<.001), accounting for 18% of the variation in SCD. In Model 2, socioeconomic status, education, and bodily symptoms were significant predictors of SCD (F (5,111) = 13.99, p<.001) and explained 39% of the variation in SCD. In Model 3, neighborhood problems, length of residence added, socioeconomic status, education, and bodily symptoms were significant predictors and contributed 44% of the total variance in SCD (F (7,109) = 12.10, p<.001). In Model 4, sleep difficulties, length of residence, bodily symptoms, socioeconomic status, and education were significant predictors of SCD (F (9,107) = 13.59, p<.001), and accounted for 50% of the variation in SCD.ConclusionGiven that Black Americans have been found to have a higher prevalence of sleep disturbances compared to white Americans, our findings could add to inform future health interventions and policy recommendations that can address modifiable sources of poorer brain health in Black men.
Cerebral systems underlying anosognosia for memory loss in aging and Alzheimer’s disease
Authors: Mimmack Kayden J. , Qiao Krystal , Gagliardi Geoffroy Pierre , Bueichekú Elisenda , Cacciamani Federica , Wang Sharon , Udeogu Onyinye , Marshall Gad A , Sepulcre Jorge , Vannini Patrizia 
Published: December 2023

AbstractBackgroundLoss of awareness of cognitive decline (a.k.a. anosognosia) is a common symptom of Alzheimer’s disease (AD) dementia and has also been observed in its predementia stages. Anosognosia is thought to be related not only to functional changes in individual brain regions, but also to a disturbance in functional connectivity (FC) between or within networks. This study aimed to investigate how memory awareness relates to resting‐state fMRI segregation (within‐network connectivity) and integration (between‐network connectivity) maps across the AD spectrum.MethodWe included 66 older adults divided in two groups: cognitively normal (CN, n = 49), and symptomatic (mild cognitive impairment or mild AD; n = 17). Memory awareness was measured as the discrepancy between the participant’s and study partner’s scores on the Cognitive Function Instrument. Positive values indicated heightened awareness and negative values indicated unawareness. We assessed whole‐brain connectivity with resting‐state fMRI and computed voxel‐level maps of segregation and integration. General linear models were used to relate the integration or segregation of each voxel to memory awareness (in the total sample and in the two groups separately), adjusted for age, sex, and education. Multiple comparison correction was performed using cluster‐wise Monte Carlo simulations.ResultDemographics are presented in Table 1. Segregation maps showed that lower awareness was associated with increased connectivity within the frontoparietal network (FPN) and with decreased connectivity within the medial visual, default mode (DMN), and sensory‐motor networks (Figure 1A(i); Table 2A(i)). The relationship with the FPN persisted in the CN and symptomatic groups separately, and an additional negative association between awareness and FC in the salience network was found in the CN group (Figure 1B‐C(i); Table 2B‐C(i)). In integration maps, lower awareness was associated with increased between‐network connectivity of the dorsal attention and DMN, and decreased connectivity of the salience and sensory‐motor networks (Figure 1A(ii); Table 2A(ii)). In the CN group, the sensory‐motor relationship persisted, while the DMN relationship reversed (Figure 1B‐C(ii); Table 2B‐C(ii)).ConclusionAnosognosia is characterized by reduced FC patterns featuring disconnection between self‐referential networks (DMN and salience) to other networks and hyperconnectivity within the FPN. Future studies should investigate the pathological underpinnings for these functional changes.
Bayesian network analysis of BIN1 risk allele and other risk factors and biomarkers of Alzheimer’s disease
Authors: Wang Jian , Rathore Saima , Morris Amanda , Lu Ming , Sabourin Jeremy , Hooli Basavaraj 
Published: December 2023

AbstractBackgroundThe Bridging Integrator I (BIN1) is a significant genetic risk gene, second only to the established risk gene apolipoprotein E (APOE4), for late‐onset Alzheimer’s disease (LOAD, AD) (Carrasquillo, 2011). BIN1 rs744733 risk allele was shown to affect tau pathology and cognitive decline (Franzmeier, 2021).In this study, we compared BIN1 risk allele rs6733839 with APOE4 on interdependency among AD risk factors and biomarkers by applying Bayesian Network (BN) modeling (Scutari, 2017) to data from Lilly AD clinical trials.MethodData from A05C (n = 142, NCT01565382), A05E (n = 217, NCT02016560), and untreated arms of AZES (n = 206, NCT02245737), LLCF (n = 229, NCT02791191), and LZAX (n = 194, NCT01900665) trial participants were used for the analysis (table 1). We constructed graphs representing the dependencies among the variables, including demographics, genetic risk genes, brain amyloid and tau measured by 18F‐Florbetapir or 18F‐Flortaucipir positron emission tomography (PET) imaging quantified globally and regionally as a standardized uptake value ratio. Longitudinal tau changes from baseline were computed for a sub cohort (n = 234). Conditional Gaussian Bayesian Network (CGBN) was used to model discrete (gender, genotype) and continuous (age, PET quantifications) variables. Directed Acyclic Graphs (DAG) structure was learned using constraint‐based Incremental Association (iamb) algorithm and score‐based Hill‐Climbing (hc) algorithm with one‐sided type I error rate at 10%. The connection strength was estimated by bootstrap resampling and computing the probability of any variable influencing another variable. Model parameters were estimated using the maximum likelihood estimation method.ResultThe result shows that age influences baseline amyloid (Strength s = 1.0) and parietal tau (s = 0.83). APOE4 influences baseline amyloid (s = 0.75) and tau at four lopes with strength ranging from 0.84 to 0.31 in the order of frontal, parietal, occipital, and temporal lobes. BIN1 influences baseline tau at the parietal lobe (s = 0.42) and other lobes with strength below 0.3. We have not observed consistent dependency between variables and change in tau, likely due to the small sample size (n = 234).ConclusionOur study result is consistent with current knowledge of APOE4 influencing amyloid and tau. The finding that BIN1 influences tau supports the observation of BIN1 rs744373, in linkage disequilibrium with rs6733839, in ADNI and BioFINDER studies (Franzmeier, 2021).
Challenges in identifying Latinos living with ADRD among newly diagnosed cancer patients
Authors: Schiaffino Melody , Moore Alison A. , Gilbert Paul E , Murphy James D , Marquine María J. 
Published: December 2023

AbstractBackgroundNavigating the complex decision‐making and coordination challenges of a cancer diagnosis is difficult for any person diagnosed with cancer. This burden can become untenable for Latinos living with Alzheimer’s and Related Dementias (ADRD). The literature has demonstrated the disproportionate burden of late‐life comorbidities on Latino populations due to a myriad of existing inequities, such as barriers related to patient‐provider communication and language, cultural and other unique needs, and social and economic factors. Identifying ADRD and social correlates of risk for ADRD and cancer in Latino patients is critical to improve treatment planning and outcomes. However, Latinos are critically underrepresented in most population‐based and nationally‐representative databases. We studied a linked claims database and tumor registry to explore variation across tumor prevalence and social correlates of Latinos living with ADRD and cancer.MethodsThis retrospective cohort study examined ADRD and cancer in Latinos using the National Cancer Institute’s SEER‐Medicare database of newly diagnosed cancer patients aged 67+ (N = 337,932). Tumor and claims‐based utilization on Latino and non‐Latino patients with and without ADRD were used to explore variation in prevalence of ADRD, cancer, and social correlates. A non‐cancer 5% sample from the same Medicare cohort was used as a control.ResultsLatinos were widely underrepresented across all tumor sites: breast, cervical, colorectal, oral, lung, and prostate. The prevalence of Latino patients with ADRD and cancer varied significantly compared to White patients. Latinos had a higher prevalence across all cancer sites with the lowest prevalence for Latinos in Prostate cancer (4.63% vs 2.33% for White patients) and the highest in Oral cancer (12.67% vs 7.82%).ConclusionThe differential prevalence of ADRD and cancer is significant in massive claims data which is a key source of nationally representative healthcare utilization and care information on older adults. Our cohort excluded dual‐eligible, metastatic, and undocumented patients. Claims and registry data lack context on language proficiency and diagnostic accuracy suggesting our substantial variation may be conservative. Improving methods and data for identifying and addressing social correlates of risk for patients with ADRD and cancer is critical for this rapidly growing and high‐risk population.