bluuebunny/crossref_metadata_2025 huggingface dataset:
Circulating metabolome in relation to cognitive impairment: a community‐based cohort of older adults
Authors: Huang Yuhui , Sun Xuehui , Huang Qingxia , Huang Qiumin , Chen Xiao , Zhou Xiaofeng , Chen Hui , Shen Jie , Gao Mengyan , Zhang Hui , Tang Huiru , Wang Xiaofeng , Jiang Xiaoyan , Zheng Yan , Yuan Changzheng
Published: January 2025

Background

The role of circulating metabolome in cognitive impairment is limited and inconclusive. We aimed to identify plasma metabolites associated with cognitive impairment and evaluate the added predictive capacity of metabolite biomarkers on incident cognitive impairment beyond traditional risk factors.

Method

In the community‐based Rugao Longevity and Ageing Study (RuLAS), plasma metabolome was profiled by nuclear magnetic resonance (NMR) spectroscopy. Participants were classified into the cognitively normal, moderately impaired, and severely impaired group according to their performance in two objective cognitive tests. A two‐step strategy of cross‐sectional discovery followed by prospective validation was applied to identify cognitive impairment‐related metabolites. In the discovery stage, we included 1643 participants (age: 78.9 ± 4.5 years) and conducted multinomial logistic regression. In the validation stage, we matched 68 incident cases of cognitive impairment (moderately‐to‐severely impaired) during the 2‐year follow‐up to 204 cognitively normal controls by age and sex with a 1:3 ratio and conducted conditional logistic regression. Metabolite set enrichment analysis was performed to identify cognitive impairment‐related metabolic pathways. We constructed prediction models for incident cognitive impairment using Lasso regression.

Result

We identified 28 metabolites cross‐sectionally related to severely impaired cognition, among which IDL particle number, ApoB in IDL, leucine, and valine were each prospectively associated with 28%, 28%, 29%, and 33% lower risk of incident cognitive impairment. Based on incident cognitive impairment‐related metabolites, three enriched metabolic pathways (valine, leucine, and isoleucine biosynthesis; valine, leucine, and isoleucine degradation; and aminoacyl‐tRNA biosynthesis) were found. Incorporating 13 metabolite biomarkers selected by Lasso regression into the traditional risk factors‐based prediction model substantially improved the prediction performance on incident cognitive impairment (AUCs: 0.839 vs. 0.703, P <0.001).

Conclusion

The study identified specific plasma metabolites and potential enriched metabolic pathways related to cognitive impairment. Utilizing the selected metabolites substantially improved the prediction performance for cognitive impairment.
Baseline plasma NfL, p‐tau217 and tau‐PET SUVr predict cognitive decline in non‐demented persons from a memory clinic
Authors: Mendes Augusto J. , Ribaldi Federica , Lathuiliere Aurelien , Ashton Nicholas J. , Janelidze Shorena , Zetterberg Henrik , Scheffler Max , Assal Frederic , Garibotto Valentina , Blennow Kaj , Hansson Oskar , Frisoni Giovanni B.
Published: January 2025

Background

Plasma biomarkers have been increasingly studied in Alzheimer’s disease due to their potentially high accessibility, affordability, and low invasiveness. Recent studies have shown that baseline plasma levels are capable of predicting cognitive decline in cognitively unimpaired subjects (CU) and with mild cognitive impairment (MCI). Despite the fact that neuroimaging biomarkers are also strong predictors, it is still unclear how well they perform when compared to plasma biomarkers in predicting cognitive deterioration.

Method

Our goal was to evaluate how plasma (i.e., p‐tau181, p‐tau231, p‐tau217, GFAP, and NfL) and traditional neuroimaging biomarkers (i.e., amyloid‐PET centiloid, tau‐PET global‐SUVr, and hippocampal volume) are able to predict cognitive decline in non‐demented individuals. A total of 100 subjects were included in this study, namely 67 MCI and 33 CU from the Geneva Memory Center cohort. The study applied linear mixed‐effect regression models to evaluate how baseline biomarker levels predict cognitive decline. Moreover, sample sizes for future AD clinical trials were calculated for a subset of amyloid‐positive subjects based on how well each biomarker could predict the disease.

Result

Cognitive decline was only significantly predicted in the MCI subsample by baseline plasma NfL (β = ‐0.53, p = 0.02) p‐tau217 (β = ‐0.59, p = 0.009), and tau‐SUVR (β = ‐0.91, p = 0.002). Lastly, we have proven that the sample sizes for future treatment trials targeting AD can be reduced by up to 70% in individuals who exhibit both amyloid‐PET positivity by incorporating NfL as a requirement for inclusion. On the other hand, the inclusion of p‐tau217 might decrease amyloid‐positive sample sizes only by 10%.

Conclusion

Tau‐SUVR was the best predictor of cognitive decline in the MCI stage, followed by plasma p‐tau217, and NfL. However, when the goal is to identify at‐risk subjects for future AD clinical trials with amyloid‐PET positivity in the inclusion criteria, the NfL seems to be the most appropriate biomarker to evaluate. This implies a strong association between amyloid‐PET and p‐tau217, whereas NfL may be more appropriate to identify individuals at‐risk for developing cognitive decline.
Circulating stress hormones and multimodal measures of brain and cognition in older adults: Cross‐sectional findings from the AGE‐WELL cohort
Authors: Liebscher Maxie , White Silke , Touron Edelweiss , Mézenge Florence , Chocat Anne , Coulbaut Laurent , Vivien Denis , la Sayette Vincent De , Marchant Natalie L , Chételat Gael , Klimecki Olga M. , Poisnel Géraldine , Wirth Miranka ,   Medit‐Ageing Research Group
Published: January 2025

Background

Increased stress, a proposed risk factor for Alzheimer’s disease (AD), is associated with increased brain and cognitive vulnerabilities in older populations, which may be different in women and men.

Objective

To examine cross‐sectional associations between circulating stress hormones (epinephrine, norepinephrine, cortisol, dehydroepiandrosterone sulfate (DHEAS), and DHEAS/cortisol ratio) and multimodal measures of brain health and cognition sensitive to AD.

Method

132 cognitively unimpaired older participants without clinical depression (age = 74.0 ± 4 years, females: n = 80) were included from the Age‐Well baseline dataset. Stress hormones were measured in overnight fasting blood serum (cortisol, DHEAS) and plasma (epinephrine, norepinephrine). The association of stress hormone levels with glucose metabolism and perfusion in AD sensitive brain regions, including the anterior and posterior cingulate cortex (ACC, PCC), insula and, precuneus, along with neocortical amyloid deposition and cognitive markers, including memory and Preclinical Alzheimer's Cognitive Composite‐5 (PACC5), was assessed. Linear regression models with and without stratification by sex adjusting for covariates of age, sex, education, subclinical anxiety, and depression were conducted.

Result

In the total cohort, higher epinephrine was associated with lower glucose metabolism (Figure 1) in the ACC (adj.‐β = ‐0.26, p = .027), PCC (adj.‐β = ‐0.32, p = .006), and precuneus (adj.‐β = ‐0.27, p = .021) and lower perfusion in the PCC (adj.‐β = ‐0.23, p = .013). Sex‐stratified analyses showed interactions (all p’s < .1): In males (but not in females), higher cortisol was associated with lower episodic memory (adj.‐β = ‐0.33, p = .02), short‐term memory (adj.‐β = ‐0.32, p = .014) and PACC5 scores (adj.‐β = ‐0.28, p =.04), suggesting a stress‐related vulnerability in the cognitive system of men. Stress biomarkers were not associated with neocortical amyloid deposition (all p’s ≥ .1).

Conclusion

Our results demonstrate the involvement of stress hormones, particularly epinephrine and cortisol, in increased vulnerability of the brain and cognition in older adults and the manifestation of sex specificities in this context. The role of stress on brain and cognitive health and related sex differences needs to be considered in intervention programs.
Enhancing Dementia Care: A Digitally Supported Care Management Program for Informal Caregivers ‐ A Cluster‐Randomized Controlled Trial
Authors: Boekholt Melanie , Klein Olga A. , Blotenberg Iris , Teipel Stefan , Michalowsky Bernhard , Kilimann Ingo , Hoffmann Wolfgang , Thyrian Jochen René
Published: January 2025

Background

Approximately 1.8 million individuals in Germany live with dementia, imposing a substantial burden on family caregivers who provide most care and often experience health issues, social isolation, and diminished quality of life. Recognizing and addressing the diverse needs of these caregivers is vital for their well‐being and the stability of care arrangements.

Method

This study employed a longitudinal, cluster‐randomized controlled trial in Mecklenburg‐Western Pomerania, Germany, with 192 informal caregivers of people living with dementia. Participants were randomly assigned to either the control (n = 96) or intervention (n = 96) group. The intervention involved a digitally supported care management program delivered by trained care managers, specifically tailored to address the unmet needs of caregivers.

Result

Primary outcomes after 6 months included the number of unmet needs and the health‐related quality of life of caregivers. Secondary outcomes comprised caregiver burden and social network/support. While the intervention did not significantly reduce overall unmet needs in multivariate models, it demonstrated a notable effect in the subgroup of younger family caregivers. No statistically significant impacts were observed on other outcomes.

Conclusion

Individualized care management, as delivered through this program, effectively addresses the specific support needs of informal caregivers. The study emphasizes the importance of tailoring interventions to sustain preferred caregiving arrangements and underscores the necessity of investigating nuanced needs for effective support. Although the program did not show a universal reduction in unmet needs, its positive impact on younger caregivers suggests potential benefits for specific demographic groups.
Longitudinal interplay between cerebral glucose metabolism, subclinical atherosclerosis and cardiovascular risk factors in midlife: the PESA study
Authors: Tristão‐Pereira Catarina , Fuster Valentin , Garcia‐Lunar Ines , Schöll Michael , Suarez‐Calvet Marc , Moro Maria Angeles , Garcia‐Alvarez Ana , Sanchez‐Gonzalez Javier , Zetterberg Henrik , Blennow Kaj , Ibañez Borja , Gispert Juan Domingo , Cortes‐Canteli Marta
Published: January 2025

Background

Cardiovascular disease and dementia often co‐exist at advanced stages. Yet, midlife longitudinal studies examining the interplay between atherosclerosis and its risk factors on brain health are scarce. We aimed to determine the longitudinal associations between cerebral glucose metabolism, subclinical atherosclerosis and cardiovascular risk factors in middle‐aged asymptomatic individuals.

Method

The Progression of Early Subclinical Atherosclerosis (PESA) is a longitudinal observational cohort study of 4184 asymptomatic individuals aged 40‐54. Participants with subclinical atherosclerosis underwent longitudinal cerebral [18F]fluorodeoxyglucose (FDG)‐PET (outcomes). Cardiovascular risk was quantified with SCORE2 and subclinical atherosclerosis with 3D vascular ultrasound (exposures). Multivariate regression and linear mixed effects models were used to assess outcome‐exposure associations through region‐of‐interest and voxelwise approaches. Additionally, blood‐based biomarkers of neuropathology were quantified and mediation analyses performed.

Result

This longitudinal study included 370 participants (median age: 49·8 [IQR=46·1‐52·2] years; 84% men; follow‐up: 4·7 [4·2‐5·2] years). Persistent high‐risk of cardiovascular disease was associated with an accelerated decline of cortical FDG uptake compared to low‐risk (β=‐0·008 [95% CI ‐0·013 to ‐0·002]; pFDR=0·040), with plasma neurofilament light chain, a marker of neurodegeneration, mediating this association by 20% (β=0·198 [0·008 to 0·740]; pFDR=0·050) (Figure 1). Moreover, progression of subclinical carotid atherosclerosis was associated with an additional decline in FDG uptake in Alzheimer’s disease brain regions, not explained by cardiovascular risk (β=‐0·269 [95% CI ‐0·509 to ‐0·027]; p=0·029) (Figure 2).

Conclusion

Middle‐aged asymptomatic individuals with sustained cardiovascular risk and subclinical carotid atherosclerosis already present brain metabolic decline, suggesting that maintaining cardiovascular health during midlife may be key to reducing neurodegenerative disease burden later in life.
The MRI signature of alpha‐synuclein pathology in preclinical stages and in a memory clinic population
Authors: Wisse Laura E.M. , Spotorno Nicola , Strandberg Olof , van Westen Danielle , Mattsson‐Carlgren Niklas , Palmqvist Sebastian , Stomrud Erik , Parchi Piero , Hansson Oskar
Published: January 2025

Background

Alpha‐synuclein pathology underlies Lewy body diseases and can also occur comorbid to other neurodegenerative pathologies. The lack of an in vivo measure for alpha‐synuclein pathology until recently has limited thorough characterization of its brain atrophy pattern, especially during early disease stages. We therefore aimed to assess the association of alpha‐synuclein pathology in cerebrospinal fluid (CSF) with magnetic resonance image (MRI) structural measures in three independent cohorts, and separately in clinically unimpaired (CU) and cognitively impaired (CI) individuals, the latter reflecting a memory clinic population.

Method

Individuals from BioFINDER‐1 (N=752), BioFINDER‐2 (N=1388) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI; N=823) with CSF alpha‐synuclein seed amplification assay results were included. T1‐weighted MRIs were processed with voxel‐based morphometry (VBM) and for region of interest (ROI) analyses with FreeSurfer 6.0 and an automated pipeline for basal forebrain nuclei CH1/2/3 and CH4/4p (=nucleus basalis of Meynert). All analyses were corrected for age, sex, intracranial volume (volumetric measures), CSF Aβ42/40 (ADNI: Aβ42), phospho‐tau181 and cognitive status (only whole cohort). Executive functioning was assessed with the symbol digit modalities test (BioFINDER‐1&2) or the harmonized composite executive function score (ADNI).

Result

In BioFINDER‐2, VBM analyses in the whole cohort revealed a specific association between alpha‐synuclein pathology and the cholinergic CH4/4p nuclei (Figure 1). Next, ROI‐based analyses, focused on regions involved in the cholinergic system, revealed that alpha‐synuclein pathology was indeed associated with smaller CH4/4p volumes, and with smaller CH1/2/3 volumes in BioFINDER‐2. Even in CU individuals, alpha‐synuclein pathology was associated with smaller CH4/4p volumes and entorhinal cortex thickness; only the former association was found in CI individuals (Figure 2). Overall, the association between alpha‐synuclein pathology and CH4/4p volume was replicated in BioFINDER‐1 and ADNI. In CI individuals, CH4/4p volumes partially mediated the association of alpha‐synuclein pathology with executive functioning in all cohorts (Figure 3).

Conclusion

The findings suggest that atrophy in relation to alpha‐synuclein pathology is restricted and clearly affects the nucleus basalis of Meynert already during preclinical stages. Further, in memory clinic populations with cognitive impairment, alpha‐synuclein pathology is also associated with nucleus basalis of Meynert atrophy, which seems to partially mediate alpha‐synuclein‐induced executive impairment.
Synuclein Aggregate Assay Performance in Autopsy‐Confirmed Lewy Body Dementia: Results from the U.S. Dementia with Lewy Bodies Consortium
Authors: Leverenz James B , Patel Purvi , Formica Shane , Bekris Lynn M. , Tsuang Debby W , Zabetian Cyrus P , Litvan Irene , Fleisher Jori E , Berman Sarah , Irwin David J , Bozoki Andrea , Lippa Carol , Lopez Oscar L. , Galasko Douglas R. ,   Dementia with Lewy Bodies Consortium
Published: January 2025

Background

Synuclein Aggregate Assays (SAA) in cerebrospinal fluid (CSF) and in skin biopsy have been shown to successfully identify underlying synuclein (Lewy body) pathology in patients with Parkinson's disease. Data in Lewy Body Dementia (LBD) is limited, particularly with pathologic confirmation and staging of underlying Lewy body pathology, and other co‐pathologies.

Method

Utilizing data and biofluids from participants in the U.S. based Dementia with Lewy Bodies Consortium (DLBC) who have donated CSF to the study and come to autopsy, we examined the performance of CSF‐based SAA and AD biomarkers during life to post‐mortem presence and staging of Lewy body pathology (LBP) and Alzheimer's disease Neuropathologic Change (ADNC). SAA testing was performed on CSF by Amprion (SynTap).

Result

Currently, the DLBC has enrolled over 160 participants, of which 31 cases have come to autopsy and been staged for LBP, ADNC, and TDP‐43 pathology. Twenty‐eight cases had CSF available from study participation. Three cases did not have LBP at autopsy and CSF SAA testing was negative in all three. Of the remaining 25 cases, two additional cases were CSF SAA indeterminate or negative and had anatomically limited LBP (brainstem and amygdala predominant respectively). One amygdala predominant LBP case had a positive CSF SAA. The remaining 22 limbic or neocortical stage LBP cases were CSF SAA positive ("detected"). SAA testing was positive in three cases with limbic or neocortical LBP and high stage ADNC co‐pathology.

Conclusion

CSF‐based SAA testing performed well in Lewy body dementia with autopsy‐confirmed limbic or neocortical stage LBP. Detection of LBP when in more limited anatomic locations, brainstem or amygdala, was less reliable. False positive CSF SAA was not observed in this autopsy confirmed sample of LBD.
Epigenomic assessment of differential pathological and clinical presentation in the Lewy body dementias
Authors: Harvey Joshua , Imm Jennifer , Creese Byron , Chouliaras Leonidas , Dempster Emma , Ballard Clive G , O'Brien John T , Aarsland Dag , Mill Jonathan , Pihlström Lasse , Pishva Ehsan , Lunnon Katie
Published: January 2025

Background

The Lewy body dementias are a class of neurodegenerative disease encompassing Parkinson’s disease dementia (PDD) and Dementia with Lewy bodies (DLB). Despite similar clinical and neuropathological profiles, the principal differentiating feature is the sequence in which symptoms develop. A question still remains as to a biological basis of this difference and a potential explanation is epigenetic mechanisms, molecular processes which alter the way in which the underlying genetic sequence is expressed.

Method

DNA methylation was quantified using the Illumina EPIC array for 932 samples from the anterior cingulate cortex (ACC, n = 462) and the prefrontal cortex (PFC, n = 470), sourced from 481 unique donors. Samples were defined based on antemortem records as neurological controls (n = 103), PD (n = 123), PDD (n = 101), DLB (n = 95) and Alzheimer’s Disease (AD, n = 59). Weighted gene correlation network analysis (WGCNA) was conducted, controlling for confounders to define co‐methylated networks with evidence of association to pathological (Braak NFT and LB) outcomes and clinical subgroups, including presentation of neuropsychiatric symptoms. Significantly associated modules were tested using gene ontology analysis (GO, missMethyl) and expression enrichment in publically available single nucleus RNA sequencing datasets (Expression Weighted Cell Type Enrichment Analysis, EWCE).

Result

11 co‐methylation modules (ACC = 9, PFC = 2) showed FDR corrected significant association to either a pathological or clinical outcome. The most significantly associated module was observed in the ACC (Figure A & B), with association with both Braak LB stage (P = 1.49 x 10‐5) and PDD presentation stratification (P = 1.41 x 10‐6). The module showed significant GO term enrichment relevant to inflammation (Figure C) and EWCE analysis confirmed expression of genes annotated to this module were significantly enriched in microglial cell types. The module contained epigenetic loci annotated to C1QB, PLA2G15 and ERGIC1, all of which showed nominal clinical groupwise association in a clinical EWAS analysis of the same cohort.

Conclusion

Epigenetic alterations show evidence of insight into brain region specific pathological processes with differential stratification between DLB and PDD. Ongoing analysis in this cohort looks to resolve sex specific stratified analyses.
Alzheimer’s disease and microbiota: The MICMALZ cohort
Authors: Bennys Karim
Published: January 2025

Background

Microbiota is modulated by normal aging, but also by Alzheimer’s disease (AD) risk factors as poor diet or alteration of sleep patterns. Patients with AD exhibit a dysbiosis characterized by changes in the relative proportions of specific bacterial phyla. Eventually, fecal microbiota transplants (FMT) can improve cognitive deficits and reduce amyloid‐ß deposition, at least in mouse models of AD.

Method

We generated a cohort of AD patients, with control participants matching on age, sex, body mass index, Mini Nutritional Assessment® and education, to sample and compare microbiota composition in the stool and blood compartments. This metagenomic study will be completed by targeted and non‐targeted metabolomic analysis to inform about microbiota impact on the host. We precisely evaluated cognition, sleep parameters and dietary habits of the subjects. Moreover, stool samples from 19 patients were pooled by 4, with similar age and sex, from each group, and were transplanted in a mouse model of AD (5XFAD, n = 94) or their control littermates (n = 113) to evaluate the consequences on gut microbiota composition, memory‐related behaviors and molecular and cellular biomarkers of AD physiopathology.

Result

We generated a cohort of well characterized patients representative of mild to moderate AD patients with 45 AD patients [age 75 (SD 0.9), 51% women, minimental state examination (MMSE) 22 (interquartile range, IQR, 17‐25)] and 37 controls [age 72 (SD 1.5), 62% women, MMSE 29 (IQR 27‐30)]. Our preliminary results indicate i) a potential dysbiosis in AD patients that translates to mouse microbiota composition following FMT. A specific bacterial genus is increased both in 5XFAD and control mice potentially indicating over‐representation in AD patients relative to the controls; ii) an impact of microbiota transplanted from AD patients to mouse model on memory and behavior, with an alteration of novel object recognition but also on biomarkers of AD pathology including an increase in mouse Aß1‐42 expression level.

Conclusion

Our results suggest that gut microbiota dysbiosis is associated with AD status and point to a specific bacterial genus. Moreover, FMT from AD patients in an AD mouse model recapitulates important features of the disease, with memory impairment and Aß1‐42 accumulations.
Single‐cell transcriptomic landscapes of neurodegenerative diseases: towards mapping shared and distinct mechanisms
Authors: Shwab Elliot Keats , Man Zhaohui , Gingerich Daniel , Garrett Melanie E , Crawford Gregory , Ashley‐Koch Allison , Chiba‐Falek Ornit
Published: January 2025

Background

Age‐related neurodegenerative disorders (NDDs) continuum includes late‐onset Alzheimer’s disease (LOAD), Dementia with Lewy bodies (DLB), and Parkinson’s disease (PD) exhibit shared and distinct clinicopathological characteristics. Each of the different NDDs is characterized by a complex genetic etiology and although numerous loci have been identified via GWAS, and the causal genes and the specific neuronal and glial cell subtypes through which they exert their pathogenic effects are yet to be fully elucidated. We aimed to untangle the genetic complexity of NDDs, and to identify shared and distinct biological pathways and disease driver cell‐subtypes across NDDs.

Method

Single‐cell transcriptomic profiling was performed using LOAD, DLB, PD and normal brains (12/group). Differential expression was analyzed using the single‐nucleus (sn)RNA‐seq datasets by Nebula. To investigate shared biological pathways, we analyzed the common DEGs across NDD pathologies for each cell‐type using Metascape and aPEAR. To identify distinct DEGs and biological pathways we comparted directly between each two pathologies. The vulnerable and disease driver cell‐subtypes were characterized by beta‐regression and AUCell analyses, respectively.

Result

We identified cell‐subtype specific differential expressed genes (DEGs) for each NDD compared to control. A catalogue of common DEGs across NDDs in each cell type showed the largest number of upregulated‐DEGs in inhibitory neurons (∼700). Pathway analysis using the shared DEGs indicated enrichment for biological pathways including, neurodegeneration, stress response, RNA and protein metabolism, and mitochondria dysfunction. Noteworthy, we observed overlap with pathways detected for NPS comorbidity. Differential gene expression analysis between LOAD vs PD identified >5000 upregulated‐DEGs in microglia followed by Astrocytes and OPC and found enrichment for pathways including oligodendrocytes maturation and myelination, while the majority of upregulated‐DEGs in PD compared to LOAD were identified in oligodendrocytes and enriched in biological terms related to protein biosynthesis and energy metabolism. We showed that microglia and oligodendrocytes cell‐subtypes are drivers of LOAD pathology whereas PD pathogenic effect is driven by excitatory neurons.

Conclusion

This study represents the most comprehensive a systematic interrogation of gene dysregulation in a spectrum of NDDs in an unprecedented cell‐subtype resolution. The results enhance our understanding of the shared and distinct genetic factors and biological processes underlying age related NDDs.
Time window for early intervention in tauopathy mouse model
Authors: Maffei Benito , O'Neill Nathaneal , Dyson Chiara , Padmasola Guru , Moreira Francisco , Leite Marco , Magloire Vincent , Kullmann Dimitri Michael , Lignani Gabriele
Published: January 2025

Background

Early changes in network activity serve as distinctive hallmarks in tauopathies such as Alzheimer’s Disease and Frontotemporal Dementia. Decades before the onset of cognitive decline, many patients experience seizures which exacerbate the condition. Despite the recognised etiological overlaps between tauopathies and epilepsies, the relationship between tau and the development of circuit hyperexcitability is unclear and needs further investigation.

Method

Using wireless EEG to record intrahippocampal local field potentials (LFP), we characterised early biophysical alterations within the hippocampus of tauopathy mice.

Result

We identified a novel transient time window where hippocampal function is disrupted before the onset of tau pathology and cognitive decline

Conclusion

A precise and robust targeting of this circuit prior to the manifestation of the disease would advance our understanding of the role of circuit excitability in tau pathology. This could serve as an early therapeutic target, offering a novel strategic approach to deter the progression of the disease.
Relationship Between Plasma Phosphorylated Tau and Tau‐PET Spatial Patterns in Thai Patients with Amnestic Mild Cognitive Impairment or Mild Dementia Due to Probable Alzheimer's Disease: A Parcel‐wise Analysis
Authors: Thanprasertsuk Sekh , Jarukasemkit Setthanan , Booncharoen Kittithatch , Luechaipanit Watayuth , Haethaisong Thanaporn , Chongsuksantikul Adipa , Supharatpariyakorn Thirawat , Likitjaroen Yuttachai , Hemachudha Thiravat , Chunharas Chaipat , Thanapornsangsuth Poosanu
Published: January 2025

Background

Tau‐PET and plasma phosphorylated tau (p‐tau) have emerged as pivotal biomarkers for Alzheimer’s disease. Despite the practical advantages of using plasma p‐tau, there is limited understanding regarding its relationship with the topographic distribution of tau‐PET, particularly within the Southeast Asian population. This study aims to elucidate the correlation between plasma p‐tau levels and the spatial patterns observed in tau‐PET among Thai patients diagnosed with amnestic mild cognitive impairment (MCI) or mild dementia due to probable Alzheimer’s disease (AD).

Methods

Thirty patients were included in this study. Correlations between plasma p‐tau and tau‐PET standardized uptake value ratio (SUVR) in each cortical region were analyzed. Patients were further stratified into low and high amyloid‐beta (Aβ) groups using Aβ centiloid (AβCL) median split for additional subgroup analyses. Plasma p‐tau217 was measured on the Mesoscale Discovery platform with the S‐PLEX Human Tau (pT217) Kit. PET tracers for tau and Aβ were PI‐2620 and 18F‐florbetaben. Brain parcellation for regional tau‐PET analyses was performed using FreeSurfer.

Results

The mean age was 69.8 ± 8.4 years, with 20 female patients (66.7%). The median[IQR] value for plasma p‐tau217 was 7.87[11.37] pg/mL. Median[IQR] values for overall tau‐PET SUVR and AβCL were 1.20[0.35] and 43.56[53.70], respectively. Figure 1 illustrates cortical regions where plasma p‐tau217 significantly correlates with tau‐PET SUVR (p<0.05), with higher color intensity indicating stronger correlation coefficients. Cortical parcels demonstrating the highest correlation coefficients include the right anterior cingulate gyrus (r=0.74, p<0.001) and superior frontal gyri in both the left (r=0.73, p<0.001) and right (r=0.72, p<0.001) hemispheres. Figures 2 and 3 depict such cortical regions in low Aβ and high Aβ groups, respectively.

Conclusions

In our study population, plasma p‐tau and tau‐PET SUVR exhibit correlations in most cortical regions, with a characteristic sparing of primary cortices. These correlations cluster in bilateral inferomedial temporal regions in the low Aβ group. In the high Aβ group, correlations are primarily observed in neocortical areas, including frontal, anterior temporal, and temporoparietal regions. This suggests that the relationship between plasma p‐tau and tau pathology may vary based on Aβ levels, providing valuable information for understanding disease progression.
Macrophage migration inhibitory factor in prodromal Alzheimer’s disease
Authors: Behfar Qumars , Behfar Stefan Kambiz , Onur Oezguer A.
Published: January 2025

Background

Alzheimer's disease (AD) presents a prolonged asymptomatic phase, providing a significant timeframe for potential intervention. Leveraging this opportunity necessitates the early identification of diagnostic and prognostic biomarkers to detect Alzheimer's pathology during predementia stages. This enables the identification of individuals likely to progress to Alzheimer's‐type dementia, allowing them to benefit from targeted disease‐modifying therapies. The primary and critical risk factor for AD is age. As cells undergo aging, they enter a senescent state characterised by morphological alterations and the release of immune signaling mediators linked to systemic low‐grade inflammation. Therefore, we conducted a search for senescence associated markers in serum and CSF and examined their link with disease progression, aligning with clinical disease staging.

Method

We assessed the levels of the available senescence‐associated secretory phenotype (SASP) factors in serum and CSF samples of cognitively normal (CN), mild cognitive impairment (MCI) and AD patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). First, we evaluated the SASP levels in clinical stage, then we examined the association between SASP and the classical AD imaging and CSF core biomarkers, and finally we assessed the effect of SASP on the disease progression toward AD dementia.

Result

CSF measures of hepatocyte growth factor (HGF), macrophage migration inhibitory factor (MIF), matrix metalloproteinase (MMP)‐3, vascular endothelial growth factor (VEGF) and serum measures of endothelial growth factor (EGF), MMP‐1, MMP‐10 and VEGF showed significantly distinguishing levels in clinical stages. We observed significant correlation between CSF measures of MIF and phospho‐tau 181 (P‐tau181) and total tau (T‐tau) and an anti‐correlation with hippocampal volume. In our longitudinal analysis, CN and MCI subjects with increased MIF showed a higher probability of progressing in the spectrum of AD dementia and a faster cognitive decline.

Conclusion

Our results supports the evidence on the role of SASP in development of AD and endorse the use of cerebrospinal MIF as a senescence‐associated prognostic indicator for AD dementia, advocating for its inclusion in the current AD biomarker scheme to encompass pathological aspects beyond amyloid and tau.
Combination of CSF synaptic biomarkers and qEEG leads to a better prediction of disease progression in Alzheimer’s disease
Authors: Kandiah Vidhusan , Gouw Alida A , Nilsson Johanna , Teunissen Charlotte , Twisk Jos W.R. , Blennow Kaj , Zetterberg Henrik , van der Flier Wiesje M. , Brinkmalm Ann , Duits Flora H.
Published: January 2025

Background

Synaptic dysfunction plays an important role in Alzheimer’s disease (AD) and cognitive decline. We investigated the association between cerebrospinal fluid (CSF) synaptic protein levels and quantitative EEG (qEEG) measures, two modalities to measure synaptic dysfunction in AD pathology. We assessed combined and independent prognostic value of both modalities for cognitive decline along the AD continuum.

Method

We included 114 subjects with SCD or MCI (n=38 with normal Aβ42 [A‐], n=38 with abnormal CSF Aβ42 [A+], and 38 patients with AD dementia) from the Amsterdam dementia cohort, with available CSF and EEG at baseline, and more than one year clinical follow‐up. We assessed associations between CSF synaptic proteins (neurogranin, β‐synuclein, neuronal pentraxin 2 [NPTX2], synaptotagmin‐1 [SYT1], SNAP25) and qEEG measures (Global field power [GFP] ‐α,‐β,‐θ; Amplitude envelope correlation‐corrected [AEC‐c] α, AEC‐c β, and phase lag index [PLI] θ), all standardized into z‐scores, using Spearman correlations. We performed linear mixed models to assess univariate and multivariate associations with cognitive decline (i.e. repeated MMSE) along the AD continuum. We used backwards stepwise selection in multivariate models and calculated marginal R‐squared to compare prognostic accuracy.

Result

There were no correlations between CSF and qEEG markers (Table 1). In univariate models SNAP25, beta‐synuclein, neurogranin, GFP alpha, beta and theta emerged as predictors of cognitive decline (Table 2). SNAP25 showed the largest effect (stB[SE]=‐0.45 [0.13], p<0.001). For GFP‐alpha and –beta effects were reversed (0.29[0.13], p<0.05 and 0.37[0.13], p<0.01 respectively). Multivariate models combining CSF and qEEG measures improved prognostic accuracy compared to CSF or EEG only models (Table 3; R2m = 19.8%, StB[SE] = 1.26[0.28] for GFP‐α, StB[SE] = 1.32[0.32] for GFP‐β, StB[SE] = ‐0.96[0.32] for SNAP25 and StB[SE] = 0.94[0.31] for NPTX2, all p<0.01).

Conclusion

CSF synaptic proteins and qEEG measures were not directly correlated to each other, but both modalities were associated to cognitive decline. This suggests they represent different aspects of synaptic pathology in AD. The combination of both modalities showed increased prognostic accuracy over CSF‐ or qEEG‐only models. Hence, the combination has potential for a more personalized prognosis in AD.
Proteomic dementia risk assessment in hypertension
Authors: Ning Yuye , Wang Zhibo , Chen Meilin , Jia Jianping
Published: January 2025

Background

Hypertension is widely prevalent and independently increases the risk of dementia. Advances in high‐throughput plasma proteomics analyzed may offer new opportunities to improve risk stratification for these patients.

Method

This study involved a proteomic analysis of plasma samples collected during the baseline recruitment of participants in the UK Biobank. Participants included in the study were those with hypertension at baseline and no history of dementia, involving approximately 3,000 unique proteins. The primary endpoint of the study was the first occurrence of dementia. The entire cohort was divided into two subsets for feature selection: 80% of the data was used for training and 20% for testing. Feature selection was conducted using least absolute shrinkage and selection operator (LASSO) regression, followed by the development of a predictive model using Generalized Linear Models. This model was then tested within the internal cohort and compared against existing clinical risk models.

Result

This study included 14,038 hypertensive patients without dementia at baseline, with an average age of 59.94 (SD 7.06) years, of which 7,552 (53.8%) were male. During a median follow‐up of 14.4 years, 575 cases (4.1%) of dementia were identified. From the training set, using LASSO regression selected 61 proteins to constitute the primary proteomic risk model (out of a total of 2,924 measured proteins). The Area Under the Curve (AUC) for predicting dementia events using the protein model was 0.836 (95% CI 0.807–0.865). In comparison, the AUC for the demographic model (Age, sex, education, and Apolipoprotein E) was 0.766 (95% CI 0.733–0.8), and the AUC for the cognitive model was 0.589 (95% CI 0.545–0.632). The combination of models yielded an AUC of 0.845 (95% CI 0.815–0.874). Additionally, the primary 61‐protein model demonstrated good calibration (Figure 2). When the entire cohort was stratified by quartiles of predicted concentration according to the model, higher predicted values were associated with increased risk of dementia (Figure 3).

Conclusion

This study has conducted a large‐scale proteomic study on the risk of dementia events in a hypertensive population. The proteomic risk prediction model offers a broad range of dynamic risk stratification and significantly outperforms common clinical feature models.
Effects of sleep quality on diurnal volumetric change of brain in older adults
Authors: Kim Jun Sung , Han Ji Won , Oh Dae Jong , Suh Seung Wan , Jo Sungman , Kwon Min Jeong , Park Jieun , Kim Jae Hyoung , Kim Ki Woong
Published: January 2025

Background

Brain volume is influenced by several factors that can change throughout the day. In addition, most of these factors are influenced by sleep quality. This study investigated diurnal variation in brain volume and its relation to overnight sleep quality.

Method

We enrolled 1,003 healthy Koreans without any psychiatric disorders aged 60 years or older. We assessed sleep quality and average wake time using the Pittsburgh Sleep Quality Index, and divided sleep quality into good, moderate, and poor groups. We estimated the whole and regional brain volumes from three‐dimensional T1‐weighted brain MRI scans. We divided the interval between average wake‐up time and MRI acquisition time (INT) into tertile groups: short (INT1), medium (INT2), and long (INT3).

Result

Whole and regional brain volumes showed no significance with respect to INT. However, the interaction between INT and sleep quality showed significance for whole brain, cerebral gray matter, and cerebrospinal fluid volumes (p < .05). The INT2 group showed significantly lower volumes of whole brain, whole gray matter, cerebral gray matter, cortical gray matter, subcortical gray matter, and cerebrospinal fluid than the INT1 and INT3 groups only in the individuals with good sleep quality.

Conclusion

Human brain volume changes significantly within a day associated with overnight sleep in the individuals with good sleep quality.
Association Between Sleep Measures and Cognition Performance: Insights from a Digital Sleep Assessment Study
Authors: Ding Huitong , Lyu Chenglin , Searls Edward , Low Spencer , Popp Zachary T , Li Zexu , Rahman Salman , Igwe Akwaugo , Ho Kristi , Hwang Phillip H , Anda‐Duran Ileana De , Thomas Robert J , Kolachalama Vijaya B. , Au Rhoda , Lin Honghuang
Published: January 2025

Background

Sleep disorders as a contributing factor to cognitive impairment have spurred growing interest. The advent of digital technology facilitates the collection of comprehensive sleep measures in a home setting. The objective of this study is to examine the association between digital sleep measures and the Montreal Cognitive Assessment (MoCA).

Method

This study included participants from the Boston University Alzheimer’s Disease Research Center (BU ADRC) Clinical Core, a longitudinal study of aging which includes the Uniform Dataset (UDS) and other Alzheimer’s Disease related clinical features. Participants were asked to wear a SleepImage Ring when they went to bed at night at least three times in a two week span at quarterly intervals. A variety of sleep measures, such as duration of unstable non‐rapid eye movement (NREM) sleep and percentage of time spent with SpO2 below 80%, were collected from the device and analyzed. Linear regression models were used to assess the associations between these sleep measures and the MoCA total score as well as individual MoCA scores. All models were adjusted for sex, age, and education to account for potential confounding factors.

Result

Our study included 75 participants from the BU ADRC (mean age: 74.9± 7.9 years; 64.0% women). On average, the SleepImage Ring was worn for 17 nights over the duration of the study (interquartile range: 6‐23 nights). As shown in Table 1, 11 sleep measures were associated with at least one MoCA item with nominal significance (P<0.05). Interestingly, the percentage of time spent with SpO2 below 80% was negatively associated with the MoCA total score (P=0.016) as well as three individual MoCA scores, including the Language – Naming (P<0.001), Delayed recall – No cue (P=0.027) and Abstraction (P=0.034).

Conclusion

Our analysis revealed multiple suggestive associations between digital sleep measures and MoCA test scores, highlighting the potential of sleep as a modifiable lifestyle factor to assess and improve cognitive health. Further studies with larger and independent samples are required to further validate these findings.
Development and Validation of Natural Language Processing (NLP)‐Based Risk Prediction Model for Cognitive Impairment in Geriatric Patients
Authors: Soleimani Laili , CHENG FU‐YUAN , Sano Mary , Kia Arash
Published: January 2025

Background

Dementia poses a significant global crisis, yet 60% of cases go undetected, particularly among specific sub‐populations. Timely diagnosis is crucial for implementing early intervention strategies. Challenges of current screening tools (e.g., Montreal Cognitive Assessment (MOCA) and Mini‐mental Status Exam (MMSE)) include their rule‐based nature, time‐consuming administration and potential bias against individuals with lower education or different socioeconomic backgrounds.

Method

In this study, we created a patient cohort within Mount Sinai Health System, identifying individuals at high‐risk for cognitive impairment using MMSE scores 23 and below. Extracting clinical notes from inpatient and outpatient settings, we applied specific sampling logic to select the last five notes for each patient before their MMSE. Utilizing word‐embedding techniques, we vectorized sentences and input these vectors into a deep neural network for Named Entity Recognition to extract clinical concepts (e.g diagnosis, signs and symptoms, medications). A psychiatrist reviewed and selected 337 features based on their frequency in the cohort and clinical relevance. Using these features, we created a map to generate feature vectors, and following a train‐test split, 70% of the data was used to train a classifier using the random forest algorithm. The remaining 30% of the cohort was employed for validation purposes.

Result

Out of 4,366 patients, with documented MMSE scores from 2011 to 2023, 73% had one MMSE, and 29% scored below 24. The developed model demonstrated an AUC ROC of 0.93. At a threshold of 0.5, it showed a sensitivity of 0.86 and specificity of 0.85 in the validation set. On the test set, the AUC ROC was 0.68, with a sensitivity of 0.62 and specificity of 0.63 at a threshold of 0.5.

Conclusion

The development and validation of this digital tool exemplify translational research that leverages Real‐World Data (RWD) from EMR. The tool aims to assist clinicians in efficient dementia detection across different stages of the disease. Our next phase involves optimizing the feature engineering, fine‐tune the model, and deploying it in the production environment. This will facilitate automated screening of geriatric patients during clinical encounters at Mount Sinai Hospital, allowing us to measure the tool’s prospective performance.
EEG biomarkers of Epileptiform Activity in Relation to Alzheimer’s Disease Biomarkers
Authors: Horvath Andras Attila
Published: January 2025

Background

Growing evidence suggests that the imbalance between excitability and inhibitory neural activity is a key aspect of cognitive decline. Subclinical epileptiform activity (SEA) has been indicated as a marker of increased cortical excitability. While SEA is considered as a benign EEG sign in the elderly population, recent studies demonstrated its role in the progression of Alzheimer’s disease. The aim of our study was to investigate the relevance and phenotype of SEA in clinically healthy elderly population.

Method

We studied 62 elderly subjects determined as healthy based on physical, neuropsychology, neuroimaging (MRI), and serological workup. All subjects underwent 24‐h Holter electroencephalography (EEG), visual analysis was conducted by two independent raters. Subjects were classified into EEG positive (EEG+) and negative (EEG‐) groups based on detecting epileptiform activity on their EEG. Neuropsychology battery and structural MRI results were compared between the groups.

Results

EEG analysis showed epileptiform activity in 26% of cases. EEG positivity was associated with significantly lower verbal and category fluency subscores on Addenbrooke Cognitive Examination (p=0,03 and p=0,01). This group also performed worse on both Trail Making Test A and B (p =0,02 and 0,003 respectively). Age and education had a significant effect on neuropsychological performance in both groups. Structural MR analysis showed significant group differences in various areas, particularly in the parietotemporal regions (p=0,001). Interestingly, EEG+ patients had larger external temporal brain volume bilaterally (p<0,001) and reduced medial parietal volume (p=0,001).

Conclusion

Presence of SEA among healthy elderly shows a discrete but significant association with decreased cognitive performance in certain subdomains, as well as a special imaging phenotype. Our results underscore the relevance of data suggesting that cortical hyperexcitability associate with parietal atrophy and preserved temporal structures. In Alzheimer’s disease, the detailed representation corresponds to the hippocampal sparing phenotype. Considering our findings, SEA might associate with an increased risk for cognitive decline even in healthy individuals.