bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validating noninvasive techniques for 11C‐ER176 PET quantification in controls and Alzheimer’s disease patients
Authors: Rossano Samantha , Talmasov Daniel , Johnson Aubrey S. , Smith Anna C. , Guzmán Diana S. , Okafor Amarachukwu , Kreisl William Charles , De Jager Philip L , Lao Patrick J. 
Published: December 2023

AbstractBackgroundNoninvasive yet accurate PET quantification methods are crucial for safe yet meaningful PET studies. [11C]ER176 is a PET radioligand that images neuroinflammation via the 18‐kDa translocator protein (TSPO), which is upregulated in activated microglia and has previously been a PET target in Alzheimer’s disease research. Currently, the gold‐standard method for quantifying ER176 PET is kinetic modeling of the dynamic PET data using the arterial input function (AIF), which is invasive and expensive. The current study explores a pseudo‐reference region (RR) technique to noninvasively quantify ER176 scans to facilitate clinical PET studies.MethodDynamic 90‐min [11C]ER176 PET scans were acquired in 11 participants, 5 controls (5M/0F) and 6 patients (3 MCI‐3M/0F; 3 AD‐2M/1F). Arterial blood data were collected throughout the duration of the scan and were used along with the dynamic imaging data to determine regional total volume of distribution (V
T) using the two‐tissue compartment model. Standardized Uptake Value Ratio (SUVR) was calculated by normalizing the radioactivity in each region by that of the reference region (cerebellar gray matter). We explored differences across methods (AIF‐derived V
T vs. RR‐derived SUVR) and across groups (controls vs. patients).ResultWithin each group, the outcome measures from AIF and RR methods were well correlated (Controls: R2 = 0.986, p < 0.001; Patients: R2 = 0.983, p < 0.001; Figure 1). Both methods showed greater TSPO expression in patients compared to controls, with mean differences in the medial temporal cortex of 14.99% between groups for V
T and 10.65% between groups for SUVR, but lower variance for SUVR compared to V
T (Figure 2). Both quantification methods showed similar regional patterns of percent differences between groups, corresponding to tau progression along Braak staging (Figure 3).ConclusionResults suggest that using the cerebellum, which does not accumulate amyloid plaques or tau aggregates until end‐stage disease, as a reference region for [11C]ER176 may be a valid method for quantifying differences between AD patients and controls compared to gold‐standard methodology. Regional increases in neuroinflammation are more reliable for SUVR than V
T in AD‐related regions. Ongoing work includes a larger sample size to further validate noninvasive PET quantification.
Physical function characteristics among older adults at high risk of developing cognitive decline
Authors: Reparaz‐Escudero Imanol , Altuna Miren , Ecay Mirian , Ros Naia , Saldias Jon , Garcia‐Sebastian Maite , Capetillo‐Zarate Estibaliz , Lopez Carolina , Clerigue Montserrat , Estanga Ainara , Etxeberria Usune , Mateo‐Abad Maider , de Asteasu MIkel Lopez‐Saez , Izquierdo Mikel , Tainta Mikel , Martinez‐Lage Pablo 
Published: December 2023

AbstractBackgroundPhysical function profiles of older adults (≥ 60years) cognitively unimpaired but at high risk of dementia (CAIDE dementia risk score ≥6) have not been well described. The CAIDE index evaluates both modifiable, cardiovascular (CVRF), and non‐modifiable risk factors such as age, sex and educational level. The association of these factors with physical function has not been thoroughly studied.MethodWe present preliminary cross‐sectional data from the first 2 (out of 4) recruitment waves of the CITA Go‐On study, a FINGER‐like multimodal intervention prevention trial. Inclusion criteria were based on age (≥60 and ≤85) and CAIDE score (≥6). Participants were categorized according to their cognitive status. Physical function assessment included gait speed, handgrip strength and maximum leg strength measured as 1 repetition maximum (1RM). We explored physical function by CAIDE scale, regarding hypertension (i.e. systolic >140mmHg or diastolic >90mmHg), hypercholesterolemia (i.e >250 mg/dL) and body mass index (BMI) as modifiable risk factors, and accounting for age, sex and educational level as non‐modifiable ones. Analysis was performed with SPSS v.29.ResultSample of 380 subjects aged 68.4 ± 5.6 years (mean, SD), 50% women, Mini‐Mental State Examination (MMSE) mean of 28.4 ±1.7 and CAIDE index mean was 7.4 ± 1.3. Of these, 91.6% were cognitively preserved, 5.5% had subjective complaints and 2.9% mild cognitive impairment. Dyslipidemia was present in 23.4%, hypertension in 46.9% and 63.1% showed BMI of overweight or obese. Univariate regression analysis showed that CAIDE index was significantly associated to maximum leg strength (1RM) (η2
= 0.05, p = 0.008), after adjusting for non‐modifiable risk factors (age η2
= 0.054, p = 0.001; sex η2
= 0.453, p = 0.001; and educational level η2
= 0.003, p = 0.333) and BMI (η2
= 0.156, p = 0.001). Handgrip strength and gait speed were not explained by modifiable factors in our sample (p = 0.12 and p = 0.53).ConclusionPhysical function as measured by maximum leg strength is associated with CAIDE dementia risk index, and most significantly with sex and BMI component, with age displaying a moderate effect. Together with vascular risk factor control, interventions on physical function are important for prevention.
Gut microbiome‐related metabolites in plasma are associated with general cognition
Authors: Kastenmuller Gabi , Wu Tong , Arnold Matthias , Hankemeier Thomas , Ghanbari Mohsen , Uitterlinden André G. , Kraaij Robert , Van Duijn Cornelia M , Kaddurah‐Daouk Rima F. , Ikram M. Arfan 
Published: December 2023

AbstractBackgroundIncreasing evidence suggests a role of metabolism in neurological disorders including Alzheimer’s disease (AD). The human metabolome is determined by genes and modifiable factors such as gut microbiota, diet, medication, and other lifestyle choices. We hypothesized that metabolites related to endophenotypes of brain health maybe derived or influenced by these modifiable factors. Identifying the determinants of metabolites associated with AD‐related endophenotypes may help to discover new targets for drugs and prevention.MethodWe profiled plasma samples of 1082 participants of the Rotterdam study for 1387 metabolites using a non‐targeted metabolomics platform. After preprocessing and quality control, plasma levels of 991 metabolites were available for analysis of 1068 cognitively normal participants. We assessed the role of metabolites in general cognition (G‐factor) and magnetic resonance imaging (MRI) markers using linear regression. Replication analysis was performed for general cognition in an independent dataset. To identify the source of brain health‐associated metabolites, we estimated the explained variance (EV) of metabolites by genes, gut‐microbiome, medication use, and clinical features using gradient boosting decision tree (GBDT). Multiple testing correction was performed based on the false discovery rate (FDR) by Benjamini Hochberg (FDR<0.05).ResultAmong the 991 analyzed metabolites, 14 showed significant associations with general cognition, 21 metabolites with total brain volume, and one with total white matter lesions. In the replication analysis of metabolites associated with cognition, 9 metabolites showed consistent association with G‐factor. While genetics explained more than 5% of the variance of all associated metabolites, for three cognition‐associated metabolites (ergothioneine, 3‐hydroxy‐2‐methylpyridine sulfate, 4‐vinylguaiacol sulfate), modifiable lifestyle factors, medication and microbiota additionally explained up to 15% of their variance, with lifestyle factors showing the largest influence. Among the metabolites associated with brain imaging phenotypes, clinical factors and medication explained more than 5% of the variance of four metabolites (3‐hydroxysebacate, 3‐hydroxybutyrylcarnitine, sphingomyelin (d18:2/24:2), unnamed metabolite).ConclusionOur study provides evidence for the association between circulating metabolites and cognition or brain imaging phenotypes in participants without cognitive impairment. The levels of these metabolites are influenced by genetics and in part by modifiable factors. Further, studies are warranted to elucidate the complex relationship between gut microbiota, diet, genome, metabolome, and cognition.
Impact of Mid‐ and Late‐Life Diabetes in the Trajectories of Cognitive Aging in a Bi‐ethnic Cohort of Mexican Americans and Non‐Hispanic White Older Adults
Authors: Vazquez Janette , Wang Chen‐Pin , Bernal Rebecca , Seshadri Sudha , Hazuda Helen , Satizabal Claudia L. 
Published: December 2023

AbstractBackgroundMidlife vascular risk factors, including diabetes, have been associated with an increased risk of Alzheimer’s disease (AD) and related dementias (ADRD). Hispanics experience both a higher burden of cardiometabolic diseases and AD/ADRD compared with non‐Hispanic White older adults. However, there is a lack of diversity in AD/ADRD research, and additional investigations are needed to understand the impact of cardiometabolic diseases in AD/ADRD disparities. We aimed to investigate the association of mid‐ and late‐life diabetes with cognitive decline in Mexican American (MA) and Non‐Hispanic White (NHW) adults.MethodWe included participants from the San Antonio Heart Study (SAHS), initiated in 1979 to examine ethnic differences in diabetes and cardiovascular disease between MA and NHW. In 1992, SAHS participants were invited to the San Antonio Longitudinal Study of Aging (SALSA), in which cognitive function was assessed using the MMSE at four time points. The latent variable mixture model implemented in Mplus was used to identify statistically distinct classes in cognitive trajectories based on repeated MMSE scores. The Bolck‐Croon‐Hagenaars method was used to test covariate differences across classes. Participants with missing data in 2 or more MMSE scores or covariates were excluded from the analysis.ResultOur analytical sample included 337 participants (52.2% MA, 60.8% women, Table 1). Two distinct classes were identified (Shannon’s entropy = 0.813). Participants within class 1 had a steeper cognitive decline (0.53‐point drop per follow‐up), whereas those in class 2 appeared more stable (0.17‐point drop per follow‐up). Compared to class 2, participants in class 1were 2.1 and 2.5 times more likely to have diabetes during midlife (p = 0.019) and late‐life (p = 0.002) respectively. In contrast, ethnic‐stratified analysis revealed significant findings only among MA (Table 2), where participants in class 1 were 2.4 times more likely to have diabetes in midlife (p = 0.023) and 1.8 times in late life (p = 0.005) compared to class 2.ConclusionDiabetes was related to a steeper cognitive decline, particularly among MAs with prevalent diabetes in midlife. These findings provide new insights into the role of vascular burden in cognitive decline disparities among MAs. Further analysis exploring additional vascular factors are underway in this unique population.
Deciphering the components of Amyloid‐beta (Aβ)‐driven dementia using a novel peptide‐focused global proteomics platform
Authors: Saxena Satya , Ye Yuanqing , Devanarayan Viswanath , Reyderman Larisa , Koyama Akihiko , Sachdev Pallavi 
Published: December 2023

AbstractBackgroundThe overlap of Alzheimer’s disease (AD) symptomology and pathology with other dementia types is a significant challenge to treatment, patient care, and new drug development. Amyloid‐beta (Aβ) peptides begin to accumulate in AD subjects over a decade prior to clinical symptoms and impair multiple cellular pathways during disease continuum. However, how the brain proteome is remodeled by Aβ burden remains an enigma. Here we compared the cerebrospinal fluid (CSF) proteomes of demented subjects with or without Aβ pathology to unveil alterations specific to Aβ‐driven dementia.MethodMass spectrometry data (PRIDE archive PXD016278) from CSF of cognitively impaired Sweden cohort subjects was reanalyzed using our de novo‐assisted workflow. Peptide raw peak area intensities were quantile normalized and log2 transformed to reduce technical variation and ensure distribution symmetry. Differentially expressed peptides were identified via analysis of covariance after adjusting for age and gender. Multiscale Embedded Gene Co‐expression Network Analysis (MEGENA) was used to explore the dysregulated network from Aβ‐driven brain proteome remodeling.ResultThe de novo‐assisted workflow significantly increased the CSF proteome depth ‐ 4,572 CSF protein groups vs 1542 protein groups reported in PXD016278 analysis. Comparison of peptide‐level CSF proteomes of demented subjects with or without Aβ pathology identified 2,014 differentially regulated peptides (q<0.2). These alterations may reflect the Aβ‐driven brain proteome remodeling in CSF. MEGENA network analysis identified several hubs and network modules. The most significantly altered ALDO‐A peptide represented a hub, a highly connected node within a network module, and exhibited high correlation with AD‐linked neurosecretory protein VGF and MAPT. The top pathways enriched in MEGENA network modules, e.g. extracellular matrix organization, cell adhesion, and neurogenesis, are consistent with other pathway enrichment analyses across other cross‐sectional studies in AD and non‐AD dementias.ConclusionThis is the first study capturing the peptide‐level alterations in CSF to reflect brain proteome remodeling by Aβ burden. This data will serve as an important resource for biomarkers demarcating AD from non‐AD.
Coronary Heart Disease, Cognitive Impairment and Patient‐Physician‐Communication: Data from the MenDis‐CHD study
Authors: Sannemann Lena , Leikert Charlotte , Müller Hendrik , Nordmeyer Laura , Peltzer Samia , Schulz‐Nieswandt Frank , Albus Christian , Jessen Frank 
Published: December 2023

AbstractBackgroundCoronary heart disease (CHD) and dementia often co‐occur in the aging population. In addition, CHD seems to increase the risk for subsequent cognitive decline, which may in turn negatively affect the prognosis of CHD. Current CHD guidelines therefore recommend appropriate diagnosis and management of comorbid cognitive impairment. Here, we present the progression and characteristics of cognitive impairment in a group of patients with CHD and their perception of care in the patient‐physician‐relationship.MethodFor the MenDis‐CHD study, n = 364 patients with CHD were recruited from cardiologic hospital departments, rehabilitation clinics and cardiologist practices in Cologne, Germany. Medical records were used to assess severity of CHD and comorbidities. The New York Heart Association (NYHA) Functional Classification was applied for estimation of heart failure‐related symptom severity. Each patient was screened for cognitive impairment (DemTect) and depressive or anxiety symptoms (HADS questionnaire) as well as for subjective cognitive deficits. Patients were asked whether cognitive impairment was discussed with the treating physician. A follow‐up was carried out after M = 3.19 [2.2‐4.2] years in n = 118 patients. We compared patients whose cognition declined based on DemTect score to those who remained stable using t‐tests/Mann‐Whitney‐U‐tests and X²‐tests.ResultAt baseline, 10.2% of patients were screened positive for cognitive impairment, while 18.4% reported subjective cognitive deficits. Patients with a decline in cognition between study visits were significantly older (M = 67.9 vs. M = 63.1, t(115) = ‐2.7, p = .009) and showed more depressive symptoms (M = 5.0 vs. M = 3.8, t(115) = ‐2.1, p = .039). They also had more severe NYHA grades (M = 2.1 vs. M = 1.7, U(102) = 2044.5, p = .011) and a concomitant cerebrovascular diagnosis was more frequent compared to patients who did not decline (20.0% vs. 4.1%, X²(1) = 5.2, p = .048). Out of those who experienced either subjective or objective impairment at baseline (n = 88), 38.6% indicated that cognitive symptoms had previously been addressed during visits with their primary attending physician and 9.1% had been actively approached by their physician in this regard.ConclusionA relevant proportion of CHD patients displayed cognitive symptoms at baseline with progression at follow‐up. Conversations about cognitive symptoms with the physician occurred only in a minority. Our data supports the importance of raising awareness about the link between CHD and cognitive impairment in physicians.
Altered Resting‐state fMRI BOLD Signal Fluctuations in the Spectrum of Alzheimer’s Dementia and in Patients with White Matter Hyperintensities
Authors: Behrenbruch Niklas , Incesoy Enise I , Bernal Jose , Menze Inga , Vockert Niklas , Kleineidam Luca , Buerger Katharina , Wolfsgruber Steffen , Spottke Annika , Fließbach Klaus , Laske Christoph , Perneczky Robert , Peters Oliver , Priller Josef , Schneider Anja , Heneka Michael T. , Wagner Michael , Tipel Stefan , Wiltfang Jens , Speck Oliver , Perosa Valentina , Yakupov Renat , Jessen Frank , Düzel Emrah , Mattern Hendrik , Schreiber Stefanie , Ziegler Gabriel , Maass Anne 
Published: December 2023

AbstractBackgroundAltered fluctuations in blood oxygen level dependent (BOLD) signal during resting‐state functional magnetic resonance imaging (rs‐fMRI) have been considered indicative of decreased cerebrovascular health. Previous studies reported changes in BOLD fluctuations associated with Alzheimer’s dementia (AD) and white matter hyperintensities (WMH). However, to date, there has been no large‐scale study involving patients with AD, mild cognitive impairment (MCI), subjective cognitive decline (SCD), and control subjects (CON) that has explored local AD‐ and WMH‐related effects in BOLD fluctuations.MethodWe calculated the voxel‐based coefficient of variation (CV: standard deviation divided by the mean) and the relative CV (rCV: CV divided by the mean CV of the whole‐brain) of the rs‐fMRI BOLD signal in the large multicentric DZNE DELCODE cohort. After spatial preprocessing, regression of movement parameters, movement spikes, and scanner drift, low‐pass filtering and exclusion of subjects with high motion, CV and rCV maps were obtained and compared with respect to (A) clinical diagnosis (AD: n = 79; MCI: n = 113; SCD: n = 314; CON: n = 192) and cerebrospinal fluid Aβ42/40 (AD: n = 41; MCI: n = 64; SCD: n = 139; CON: n = 77); and (B) effects of vascular‐related lesions, here WMH.ResultThe CV and rCV of the precuneus and middle cingulum indicated increasingly reduced BOLD fluctuation across the clinical groups towards AD. Interestingly, we observed increases in rCV in the basal ganglia and frontal white matter in AD compared with CON. Of note, lower CSF Aβ42/40 (more pathological) was associated to reduced CV and rCV in the precuneus and with lower rCV in the right angular gyrus. Subjects with higher WMH volume showed widespread reductions of CV in white matter near the left angular gyrus and reduced rCV in large portions of white matter and subcortical gray matter.ConclusionThe AD spectrum exhibits altered BOLD fluctuations that are at least partially tied to actual amyloid differences. Larger WMH are associated with reduced BOLD signal fluctuations consistent with widespread white matter pathology ‐ beyond the effects of diagnosis. We argue that rCV is a useful complement to CV to detect these changes that might reflect cerebrovascular impairment.
Prevalence of dementia risk factors in the first 150 patients of the Oxford Brain Health Clinic
Authors: Blane Jasmine , Gillis Grace , Griffanti Ludovica , O'Donoghue M Clare , Mitchell Robert , Fossey Jane , Martos Lola , Raymont Vanessa , Mackay Clare 
Published: December 2023

AbstractBackgroundPersonalised risk reduction is a key driver for the nascent UK Brain Health Clinic (BHC) network, with increasing evidence that modifying dementia risk could delay or prevent disease progression. Livingston et al. (2020) demonstrated a number of risk factors for dementia, including less formal education (identified as no secondary education), excessive alcohol consumption (>21 units/week), obesity (BMI >30), depression and presence of an ApoE Ɛ4 allele; whilst increased physical activity has been associated with reduced risk and sleep duration is suggested to have a U‐shaped association with dementia risk. The aim of this study was to understand the prevalence of these risk factors within a typical UK memory clinic population.MethodThe Oxford BHC is a joint clinical and research assessment service for Oxford Health NHS Foundation Trust memory clinic patients (O’Donoghue et al., 2022). It aims to provide detailed clinical assessment and equal access to research opportunities. Between August 2020 and May 2022, 152 BHC patients (93.2%) consented to their clinical data, including subsequent diagnosis, being used for research purposes (mean age = 78.2 years, range 65‐101 years; 52.6% female). Self‐reported questionnaires collected education (N = 124), alcohol consumption (M SASQ, N = 150), depressive symptoms (PHQ9, N = 148), physical activity (IPAQ, N = 152) and sleep (PSQI, N = 152). BMI was calculated from height and weight measured at BHC appointment (N = 146) and ApoE Ɛ genotyping from saliva sampling (N = 76).ResultPreliminary results show 7% of patients reported no formal qualifications, 1% consumed 6 or more units of alcohol daily/almost daily, 15.7% had a BMI >30 and 45% showed mild‐severe symptoms of depression. Inappropriate sleep was reported by 13%, 71% engaged in less than 150 minutes of physical activity a week and 41% had an ApoE Ɛ4 allele (see Figure 1).ConclusionIn this population, we found a relatively small prevalence of low education and alcohol consumption, but a large proportion of patients could benefit from interventions focused on improving mood and physical activity. Ongoing analysis aims to create a weighted composite risk score for this population and explore relationships with primary diagnosis, cognition and measures of brain health including hippocampal volume and white matter hyperintensities.