bluuebunny/crossref_metadata_2025 huggingface dataset:
Cognitive profile of post‐COVID19 syndrome patients after cognitive rehabilitation on a six‐month follow‐up study in a public Brazilian center
Authors: Spera Raphael Ribeiro , de Luca e Tuma Raphael , Rodrigues Júlia Chartouni , Peixoto Satiko Andrezza Takano , Neto Adalberto Studart , Miotto Eliane C , Coutinho Artur Martins , Brucki Sonia Maria Dozzi
Published: January 2025

Background

Post‐COVID19 syndrome is characterized by signs and symptoms that occur within 3 months of the onset of COVID19 acute phase and last at least 2 months. In the past 3 years, cognitive impairment has frequently been associated with COVID19 with descriptions of attentional, executive, memory, and language disorders. Many studies have assessed these cognitive disturbances using online and telephone tests, often in isolated interviews on a cross‐sectional design in high‐income countries. Few studies evaluated the role of cognitive rehabilitation in this situation.

Method

Objective: To characterize the cognitive profile and psychological batteries of this population pre‐and post‐cognitive rehabilitation after 6 months. We selected patients younger than 65 years of age with COVID19 and cognitive symptoms for more than 3 and less than 6 months and no records of previous neurodegenerative or severe psychiatric diseases. They were evaluated 3 times (0, 3, and 6 months) with cognitive battery tests and questionnaires and later by a neuropsychologist for evaluation and cognitive training.

Result

46 patients were recruited; 41 matched the inclusion criteria and were referred to cognitive rehabilitation. 33 finished the third medical assessment. General and demographic data are shown in Table 1. Cognitive assessment in the first evaluation is demonstrated in Table 2. Only 32% of the sample had an unremarkable evaluation, and 68% were classified as having Cognitive impairment no dementia (CIND). Table 3 demonstrates patients that completed the follow‐up and the changes in cognitive tests at 6 months after rehabilitation, showing a statistically significant (p<0,05) improvement on some specific tests and questionnaires: Forward digit span, delayed memory on brief cognitive screening battery, lexical fluency (F‐A‐S), Boston naming test‐15, cognitive function instrument, geriatric anxiety inventory, and geriatric depression scale.

Conclusion

Post‐COVID‐19 syndrome and cognitive impairment are relatively common also in mild infection and healthy adult patients. After cognitive rehabilitation, we depicted significant results in attention, episodic memory, verbal fluency, and psychiatric symptoms.
Multi‐omics QTL provide insights into cell specific effects on molecular functions and intermediate traits in Alzheimer’s disease and its iPSC‐derived model systems
Authors: De Jager Philip L. , Wang Gao
Published: January 2025

Background

We examined AD‐associated loci to demonstrate how the new FunGen‐xQTL resource reveals new insights into the sequence of events leading from health to the amyloid and tau proteinopathies that define AD, as well as subsequent cognitive decline.

Method

We utilized FunGen‐xQTL resources (including cell subtype‐specific eQTL results) to deconstruct the genetic regulation and cellular specificity of AD loci. Using transcriptomic and proteomic data systematically derived from iPSC‐derived neurons and astrocytes in up to 48 iPSC lines we highlight and further dissect those genetic effects that replicate in the proper induced iPSC‐derived neuron (iN) or astrocyte (iAstro) model system.

Result

We will discuss illustrative results from our analyses, such as an interaction of CD33 and TREM2: the CD33 risk allele influences the abundance of the CD33 protein isoform and also affects the abundance of TREM2 protein in trans on the same cell surface. Further, in the APOE locus, the e2, e3, e4 haplotypes influence AD risk but not gene expression. We discovered a novel microglial‐specific eQTL for APOE driven by a variant that is not in linkage disequilibrium with APOEe4. Unlike APOEe4, this variant is not associated with AD susceptibility, but it is associated with cerebral amyloid angiopathy (CAA). Thus, APOE expressed by microglia is implicated in the emergence of CAA. Finally, we find that many neuron‐ and astrocyte‐specific QTLs discovered in single nucleus‐derived brain data, replicate in iN and iAstro. However, some eQTLs ‐ such as one affecting MAPT ‐ were significant in both datasets but had an opposite effect size in the iAstro/iN vs. the brain.

Conclusion

Our findings highlight how the FunGen xQTL integrated resource facilitates the discovery and elaboration of the causal chain linking a genetic variant to a series of molecular phenotypes and ultimately a clinical syndrome. We will gradually expand this foundation to map how AD loci interact with one another to perturb the molecular state of the brain and eventually lead to cognitive decline.
Novel mechanisms of cytosolic phospholipase A2 beta in neurodegeneration and cognitive impairments of Alzheimer’s disease
Authors: Ma Qiulan , Ebright Brandon , Li Jing , Dikeman Dante , Sanchez Ashley , Galvan Jasmin , Badie Daniel , Li Boyang , Wang Shaowei , Kerman Bilal Ersen , Hawes Debra , Hurth Kyle , Bennett David A. , Arvanitakis Zoe , Louie Stan G , Yassine Hussein N
Published: January 2025

Background

Synaptic loss predicts cognitive decline in Alzheimer’s disease (AD). However, the critical disease modifying molecular mechanisms of synaptic failure remain elusive. Animal studies implicate the increased activation of cytosolic phospholipase (cPLA2) activation in synaptic loss and neuroinflammation. cPLA2 activation in human brain synapses have not yet been demonstrated. cPLA2 preferentially catalyzes the conversion of arachidonic acid (AA) to generate eicosanoids: lipid mediators of inflammation. Synaptosomes represent an excellent ex vivo model to study synaptic function in humans. Both PSD‐95 and CamKII are synaptic markers that play essential role in learning and memory. In this study, we sought to determine whether cPLA2β is associated with synaptic markers, AD pathology and cognition in synaptosomes derived from human brain tissues.

Method

cPLA2β expression was analyzed in synaptosomes isolated from midfrontal cortex of postmortem brains in participants with no cognitive impairment (NCI, n = 20), mild cognitive impairment (MCI, n = 14) and AD (n = 19) from the clinically and pathologically well‐characterized Religious Orders Study (ROS). Experimental methods included Western blotting, immunofluorescence staining, and liquid chromatography‐tandem mass spectrometry to measure AA and its metabolites.

Result

cPLA2β was increased in synaptosomes/synapses of both MCI (*p < 0.05) and AD (***p < 0.001) compared to NCI. cPLA2β was inversely corelated with global cognitive function (r = ‐0.3667, **p < 0.01), and positively correlated with neurofibrillary tangles (r = 0.2877, *p < 0.05). Interestingly, cPLA2β was highly positively correlated with postsynaptic proteins of PSD‐95 (r = 0.7901, ****p < 0.0001) and calcium/calmodulin dependent protein kinase II (CaMKII, r = 0.2825, *p<0.05). Immunofluorescence staining revealed the colocalization of cPLA2β with phospho‐tau (AT8), synaptic PSD‐95 and CaMKII in both AD and NCI brains. cPLA2β stained degenerative excitatory neurons. On a functional level, cPLA2b was positively correlated with AA (r = 0.5203, *p = 0.01) and its inflammatory metabolites of PGD2 (r = 0.496, *p<0.05) and PGE2 (r = 0.4623, *p<0.05).

Conclusion

This is the first report revealing increased expression of cPLA2β in synaptosomes from brains with MCI and AD compared with controls. cPLA2β is associated with tau pathology, AA and its metabolites, synaptic and cognitive performance. Whether reducing cPLA2b reverses AD pathology merits further investigation.
Attention mechanism‐based prediction of early tau accumulation using MRI
Authors: Kim Jin‐Yang , Song Yeong‐Hun , Lee Wha Jin , Seong Joon‐Kyung ,   ADNI
Published: January 2025

Background

Assessing tau accumulation in early affected areas like the lateral entorhinal cortex (EC) and inferior temporal gyrus (ITG) enables early prediction of disease progression and cognitive decline. However, positron emission tomography (PET) imaging poses radiation exposure and cost concerns. This research aims to develop a deep learning model predicting tau positivity in these regions using MRI.

Method

In this study, we used the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort, of which dataset was partitioned into train, validation, and test sets (8:1:1 ratio), encompassing a total of 1010 scans, all of whom underwent T1‐weighted magnetic resonance imaging (MRI) and [18F] flortaucipir‐PET imaging. For the T1‐weighted MRI images, FreeSurfer v7.2 was employed to perform pre‐processing and extract cortical thickness measurements. Simultaneously, [18F] flortaucipir‐PET imaging was processed to compute voxel‐wise regions of interest (ROIs) for 66 specific brain regions. Regional tau positivity was established using a cutoff at a z‐score of 1.25, with a focus on cognitive normal (CN) subjects within the train set. To predict early tau accumulation regions, we developed an attention mechanism‐based encoder‐decoder model by adopting a Transformer model into our problem setting, performing sequential predictions for each of the 66 regions. Notably, the model’s predictive performance in initial regions significantly influences subsequent predictions. Consequently, we implemented a prioritization strategy, emphasizing predictions from areas where the model demonstrated high accuracy. This approach was designed to enhance the overall predictive accuracy of the model.

Result

Predicting five early tau accumulation regions per hemisphere, our model achieved an average AUC of 0.84 and accuracy of 84% for the test dataset (112 participants). Notably, in critical early disease progression regions (fusiform gyrus and ITG), AUC values of 0.84, 0.85, and accuracies of 84.4%, 84% were observed. Furthermore, the proposed prioritization strategy improved performance compared to predictions using vanilla attention‐based model.

Conclusion

We developed an attention mechanism‐based architecture with an encoder‐decoder structure. By predicting outcomes not only based on cortical thickness values but also their cross‐attention‐based contexture information, we could achieve highly accurate tau prediction in early and challenging regions
Everyday functioning in young onset dementia: differences in diagnostic groups independent of disease stage
Authors: Weltings Emma , Postema Merel C. , Tewolde Mukrabe E. , Duits Flora H. , Lemstra Afina Willemina , van der Flier Wiesje M. , Pijnenburg Yolande A.L. , Sikkes Sietske A.M
Published: January 2025

Background

Young onset dementia (YOD) is characterized by an atypical clinical manifestation, and it is unclear to what extent impairments in everyday functioning are part of this manifestation. This study aims to describe the prevalence and differences of difficulties in instrumental activities of daily living (IADL) in YOD.

Methods

In this cross‐sectional study, 394 subjects with sporadic YOD (onset<65 years,mean(M)age 58.4±standard deviation(SD)4.4 years;49.2% female) were included from the Amsterdam Dementia Cohort (ADC). Diagnoses were established in multidisciplinary consensus meetings according to disease‐specific diagnostic criteria. Everyday functioning was assessed using the proxy‐based Amsterdam IADL Questionnaire (A‐IADL‐Q). Linear regression analyses were performed to assess differences between YOD subtypes in IADL with group (YOD subtypes with AD as reference group) and IADL as outcome, adjusted for age, sex, education and disease severity (Mini Mental State Examination). A bifactor analysis was performed to identify item clusters and explore differences between groups (using linear regression).

Results

The majority of sporadic YOD were diagnosed with Alzheimer’s Disease (AD,n = 291(74%)), followed by Dementia with Lewy Bodies (DLB,n = 25(6%)), behavioral variant Frontotemporal Dementia (bvFTD,n = 49(12%)), Primary Progressive Aphasia (PPA,n = 20(5%)) and semantic variant Primary Progressive Aphasia (svPPA,n = 9(2%)). Most IADL difficulties were observed in DLB ((M) A‐IADL‐Q 41.8±(SD)7.78, reflecting moderate problems), and the fewest in PPA ((M)59.9±(SD)6.62, reflecting no problems)(Figure 1). When compared to AD (reference group), multiple linear regression analysis confirmed lower IADL scores for DLB (β = ‐6.37, SE = 1.63,p≤0.001), and higher for PPA (β = 10.29, SE = 1.76, p≤0.001), and svPPA (β = 6.83, SE = 2.61,p = 0.009), after adjustment for all covariates and confirmed in post‐hoc testing (Table 1). The bifactor analysis showed good reliability of the A‐IADL‐Q (Omega (ω_total) = 0.833), suggesting the presence of an underlying unimodal construct. Additional item clusters (Table 1) showed differences across groups, e.g. bvFTD showed more impairments in household activities compared to AD (β[95%CI] = ‐3.12 [‐5.64 – ‐0.61]). Further activity‐level differences can be found in Figure 2.

Conclusions

Our results suggest that YOD‐subtypes differ in everyday functioning difficulties, independent of disease stage. These findings contribute to the understanding of everyday functioning difficulties in YOD, ultimately contributing to earlier recognition of the disease and personalized care.
Norming and standardization of Hong Kong Brief Cognitive Test and diagnostic study on the effectiveness of screening patients with cognitive impairment
Authors: Zheng Yaonan , Chan Helen Y. L. , Li Nan , Zhu Jiahui , Pei Minyue , Yu Xin , Shi Chuan , Wang Huali
Published: January 2025

Background

The Hong Kong Brief Cognitive Test (HKBC) has solved the problems of limited population, insufficient coverage of cognitive domains and copyright limitation of previously used cognitive function test tools, which has a preliminary research basis for promotion. To make HKBC more widely used, it is necessary to collect normative data from different regions to make it have reference standards.

Method

From September 2019 to December 2021, 2312 aged 40 years and older people were recruited from different regions of China as norm construction participants. The diagnostic study included 93 normal elderly patients and 224 patients with cognitive impairment (including 156 patients with mild cognitive impairment and 68 patients with Alzheimer’s disease). Multinomial regression model was used to analyze the correlation between HKBC score and age, sex, living area and education level. The norm of HKBC total score and T score (HKBC‐T) were constructed. Based on the receiver operating characteristic curve, the AUC, sensitivity, specificity and Youden index of HKBC‐T were calculated to determine the optimal cutoff value of cognitive impairment.

Result

The results showed that HKBC score was negatively correlated with age (SE = 0.007, β = ‐0.067, P < 0.001) and positive correlation with education (SE = 0.016, β = 0.280, P < 0.001), no significant association with gender and living area (p > 0.05). According to different ages and education levels, norm of HKBC total score and HKBC‐T were constructed, and the conversion equation of HKBC‐T was calculated. The results of HKBC‐T showed a good AUC value of 0.85 in distinguishing patients with cognitive impairment from normal elderly people. The optimal cutoff value for the diagnosis of cognitive impairment by the HKBC‐T was 46 points (sensitivity = 0.914, specificity = 0.667).

Conclusion

The HKBC score is influenced by age, living area and education level, which provides a scientific basis for the development of HKBC norm model. The results of the diagnostic study showed that the optimal cutoff value of the HKBC‐T was 46 when distinguishing patients with cognitive impairment from the normal elderly.
Genome‐wide investigation of a neuropathological cohort offers novel insights in the genetic risk underlying hallmark and co‐morbid lesions implicated in Alzheimer’s disease
Authors: Laureyssen Celeste , Gawor Klara , Van Dongen Jasper , Küçükali Fahri , Koper Marta J , Ronisz Alicja , Otto Markus , von Arnim Christine , Van Damme Philip , Vandenberghe Rik , Thal Dietmar Rudolf , Sleegers Kristel
Published: January 2025

Background

Alzheimer’s disease (AD) is a heterogenous disease with a strong heritability. Genetic studies are of irreplaceable value in elucidating the mechanisms that underly this disease. The classical genome‐wide association studies (GWAS) rely on ever‐increasing sample sizes and utilize clinical AD diagnosis to investigate genetic risk. Here, we aim to eliminate phenotypic heterogeneity by performing GWAS on a deeply phenotyped neuropathological cohort.

Method

Phenotypic data regarding hallmark and co‐morbid AD lesions was collected on 721 individuals. DNA was extracted from frozen or paraffin‐fixed cerebellar tissue. Subsequently, genetic data was generated using low‐coverage whole‐genome sequencing (lcWGS) followed by imputation based on 1000 Genomes Project reference panel using GLIMPSE. Linear or logistic regression was performed in PLINK correcting for age, gender and the first 3 PCs for every phenotype. Investigated phenotypes include but are not limited to: Amyloid phases, Braak‐NFT stage, cerebral amyloid angiopathy (CAA) severity and type, pTDP presence in CA1 and dentate gyrus, alpha‐synuclein spread/presence, age‐related tau‐astrogliopathy (ARTAG) and Hirano bodies.

Result

We discovered genome‐wide significant hits for well‐established AD lesions such as tau tangles, amyloid plaques and CAA. Furthermore, significant hits for co‐morbid lesions like alpha‐synuclein stages, granulovacuolar degeneration and Hirano bodies (extracellular actin aggregates in the CA1) were found. Suggestive associations were discovered for pTDP and ARTAG. Associated loci included proof‐of‐concept findings such as strong relations between amyloid and CAA with APOE SNPs, but also included several loci that have not been previously linked to the specific phenotype or AD in general.

Conclusion

Implementing phenotypic information on neuropathological lesions in a hypothesis‐free genome‐wide investigation as a preliminary screening rendered genome‐wide significant and suggestive loci which can contribute to a deeper understanding of the individual lesions observed in AD. From our preliminary results we observe the benefits of accurate phenotyping on GWAS power. Despite small sample size, we managed to detect genome‐wide significant associations for AD‐related lesions by eliminating phenotypic heterogeneity. Associated loci will be subjected to gene prioritization and functional validation analysis to determine the causal risk genes. For more commonly investigated hallmark lesions, replication analysis will be performed in publicly available cohorts.
Regional microglial activation differs across the cortex of patients in the Alzheimer’s disease trajectory: A cross‐sectional study
Authors: Tuil Marie Emilie , Calsolaro Valeria , Crook Harry , Femminella Grazia Daniela , Pasqualetti Giuseppe , Buckley Christopher , Trigg William , Gentleman Steve , Brooks David J , Jogaudaite Simona , Abarrategui Javier Alegre , Hinz Rainer , Edison Paul
Published: January 2025

Background

Microglial reactivity and neuroinflammation are crucial pathological processes in Alzheimer’s Disease (AD). Several attempts to develop a treatment by supressing the immune response in AD have been made, yet these yielded very limited results. Recent studies suggest contrasting effects of microglial reactivity, indicating a biphasic response with both beneficial and deleterious effects at distinct stages of AD.

We evaluated the regional differential influence of microglial reactivity on neuropathological processes across AD trajectory.

Method

48 patients were divided by diagnosis into control (11), Mild Cognitive Impairment (MCI, 14), and AD (23) groups. They underwent TSPO‐PET imaging, magnetic resonance imaging (MRI), and neuropsychological testing. The spectral analysis generated a TSPO‐PET impulse response function at 90 minutes (IRF90), reflecting its volume of distribution. Region of interest and voxel‐level analyses were performed, and grey matter (GM) volume was calculated using FreeSurfer and voxel‐based morphometric analysis. Additionally, post mortem brain tissue from 27 patients at Braak Stages IV‐VI was stained for CD32a and CD163, markers of pro and anti‐inflammatory activation respectively.

Result

The AD group showed increased microglial reactivity in the temporal, parietal, occipital, and medio‐temporal lobes, and the cingulate cortex compared to controls. Voxel‐wide analyses of AD and MCI patients yielded similar results across the cortex.

The voxel‐wise analysis revealed both positive and negative clusters of association between tracer uptake and GM volume, with negative associations more often found in regions affected earlier in AD trajectory. This dual effect is further denoted by the presence of both CD32a‐positive and CD164‐positive microglia within the same regions in post mortem tissue.

Conclusion

The contrasting effects of reactive microglia on different pathological processes show regional disparities, with deleterious effects more closely associated with regions affected in the early stages of AD. This suggests a diverging response driven by both anti‐ and pro‐inflammatory reactivity profiles. The former, neuroprotective, would emerge locally alongside early pathology, while the later, neurotoxic, would only appear with more advanced pathology.

Consequently, potential treatments should promote anti‐inflammatory polarization and supress pro‐inflammatory activation in microglia for an effective therapeutic strategy.
Association of Neuropsychiatric Symptoms and General Psychopathology with Markers of Neurodegeneration in the General Population
Authors: Etteldorf Rika , de Vries Folgerdiena M. , Ettinger Ulrich , Breteler Monique M.B.
Published: January 2025

Background

Mental disorders have been linked to an increased risk of developing dementia including Alzheimer’s disease. However, previous studies have typically focused on individuals who meet diagnostic criteria for a given psychiatric disorder. The goal of our study was to examine whether diverse neuropsychiatric symptoms are related to early markers of neurodegeneration in the general population.

Method

The analysis was based on 8,318 participants (aged 30‐95) from the population‐based Rhineland Study. Neuropsychiatric symptoms (perceived stress, depressive symptoms, anxiety symptoms, attention deficit hyperactivity (ADHD) symptoms, obsessive‐compulsive disorder (OCD) symptoms) were measured using self‐report questionnaires. A general psychopathology factor was generated using principal component analysis (PCA). Cognitive performance was measured across different cognitive domains. Whole‐brain and regional brain volumes as well as white matter hyperintensities (WMH) were obtained from magnetic resonance images (3T Siemens MAGNETOM Prisma). Plasma neurofilament light chain (NfL) levels were assessed using Quanterix’s Simoa NF‐light™ assay. Relations of symptom scores with markers of neurodegeneration were quantified using multivariable linear regression models. We performed a sensitivity analysis by excluding participants reporting a neurodegenerative or psychiatric disease (n = 1,784).

Result

Participants with more severe neuropsychiatric symptoms and higher scores on the psychopathology factor performed significantly worse in all fluid cognitive domains (standardized beta coefficients (β) range between ‐0.01 and ‐0.06). The strength of association between neuropsychiatric symptoms and cognitive performance increased with age. Furthermore, neuropsychiatric symptoms (except for ADHD symptoms) and general psychopathology were associated with smaller grey matter volume (β between ‐0.00 and ‐0.02). Perceived stress, depressive symptoms, and anxiety were additionally associated with higher WMH load (β between 0.02 and 0.04), while OCD symptoms were associated with thinner cerebral cortex (β = ‐0.05 [‐0.07, ‐0.02]). Sensitivity analysis showed robustness of the associations. We found no associations between neuropsychiatric symptoms and NfL levels.

Conclusion

Various neuropsychiatric symptoms and a generally higher level of psychopathology are associated with poorer cognitive performance, grey matter atrophy, and WMH burden, even in adults without a psychiatric diagnosis. However, we did not find direct evidence of neuroaxonal injury, as indicated by the absence of an association with NfL.
Exploring Ancestry‐dependent Regulation of Alzheimer’s disease‐associated genetic risk factors in iOligodendroglia
Authors: Ramirez Aura M , Shepherd Jihanne J , Coombs Lauren , Simon Shaina A. , Moura Sofia , Rajabli Farid , DeRosa Brooke A. , Whitehead Patrice L. , Adams Larry D. , Starks Takiyah D. , Illanes‐Manrique Maryenela Z. , Tejada Sergio J. , Byrd Goldie S. , Cornejo‐Olivas Mario , Feliciano‐Astacio Briseida E. , Wang Liyong , Jin Fulai , Dykxhoorn Derek M. , Griswold Anthony J. , Young Juan I , Vance Jeffery M.
Published: January 2025

Background

Genome‐wide association studies (GWAS) in Alzheimer’s disease (AD) are consistently discovering genetic variants linked to the risk of developing this neurodegenerative condition. However, the effect size of the shared associated loci varies across populations as well as each population can have unique associations. This phenomenon could be explained by ancestry‐dependent changes in the genomic regulatory architecture (GRA) influencing the expression of these genes, similar to the effect of different local ancestry on the risk of AD in APOE4 carriers. Thus, understanding of GRA in the context of AD is imperative but currently most GRA data available is predominantly European, limiting our ability to comprehensively interpret the variability associated with AD risk genes across populations. For this study we focused on oligodendroglia, a cell lineage that has been historically overlooked but that is emerging as key players in AD due to their involvement in various pathological processes, including neuroinflammation, oxidative stress, and synaptic dysfunction. Here, we report ancestry‐dependent differences in the GRA of iPSC derived oligodendroglia with African, Amerindian, or European global ancestry.

Method

We obtained PBMCs from individuals with Alzheimer’s disease (AD) or without cognitive impairment, each with over 85% global ancestry of a specific ancestral background. These cells were then transformed into induced pluripotent stem cells (iPSC) and subsequently differentiated into oligodendroglia‐containing 3D neural cultures. On the 76th day of differentiation, we harvested and lysed the cells to isolate nuclei for Multiomic profiling including Single Cell ATAC and Single Cell RNA‐seq, we analyzed the chromatin accessibility and transcriptomes to identify ancestry‐dependent changes genome‐wide and in AD GWAS hits.

Result

We found several AD GWAS hits differentially expressed between ancestries in OPCs and in the more mature oligodendrocyte population (including APP and CLU) and some differentially accessible peaks associated to some of these genes (predominantly PRDM7). Nevertheless, OPCs showed more ancestry‐specific regulation than the more mature oligodendrocytes.

Conclusion

Our findings offer ancestry‐specific understanding of oligodendroglia chromatin changes and gene regulation in the context of AD. These results present a comprehensive perspective on the genetic regulatory architecture of oligodendroglia and constitute a resource for gene identification studies in the African American and Hispanic populations.
Exploring how genetic variation within Aquaporin‐4, influences the relationship between sleep and amyloid beta
Authors: Porter Tenielle , Armstrong Ayeisha Milligan , Dore Vincent , O’Brien Eleanor K. , Bourgeat Pierrick , Maruff Paul , Rowe Christopher C. , Smith Stephanie Rainey , Villemagne Victor L , Laws Simon M. ,   The AIBL Research Group
Published: January 2025

Background

The glymphatic system has been suggested as an important clearance mechanism for amyloid‐β (Aβ) during sleep. Animal and cellular models have suggested this clearance mechanism involves the water‐channel protein, Aquaporin‐4 (encoded by the AQP4 gene), located primarily in the astrocytic end‐feet. We have previously reported on the interaction between genetic variants within AQP4, sleep and cross‐sectional cortical amyloid‐β (Aβ) burden. This study investigated how the relationship between AQP4 genetic variants and sleep may further influence changes in cortical Aβ levels.

Methods

The current study assessed cognitively unimpaired individuals enrolled in the Australian Imaging, Biomarker and Lifestyle (AIBL) Study of Ageing, who were considered Aβ accumulators (n = 319). Aβ accumulators were defined as those who had a high baseline level of cortical Aβ (centiloid ³20), or a positive rate of change in cortical Aβ, calculated using a minimum of 3 study time‐points. 13 AQP4 gene variants were selected for analysis based on fine mapping of the gene region, and sleep was assessed using measures calculated from the Pittsburgh Sleep Quality Index (PSQI) questionnaire. The relationship between AQP4 gene variants and rate of Aβ accumulation was investigated using linear regressions. Additional linear regression models with AQP4 variant x sleep measure interaction terms and post‐hoc simple slopes were analysed to assess how these relationships may influence Aβ accumulation.

Results

AQP4‐rs68006382 was associated with Aβ accumulation, where minor allele carriers/homozygotes were observed to have a higher rate of accumulation when compared to major allele homozygotes. Linear regressions with AQP4 variant x sleep measure interaction terms revealed that in AQP4‐rs68006382 minor allele carriers there was a significant relationship between Aβ accumulation and sleep quality. Additionally, interaction analysis revealed a relationship between Aβ accumulation and sleep latency in AQP4‐rs3875089 minor allele carriers.

Conclusion

The results of this study confirm our previous findings and suggests that interactions between AQP4 genotypes and sleep measures are also associated with the rate of Aβ accumulation.
Astrocyte reactivity and cerebral glucose hypermetabolism in early Alzheimer’s: insights from a longitudinal study in the TgF344‐AD rat model
Authors: de Lima Amanda Muliterno DominguesLourenço , da Rocha Andreia Silva , Machado Luiza Santos , Soares Carolina , Ferreira Pamela C.L. , Bellaver Bruna , da Silva Patrícia Eduarda Carvalho , Venturin Gianina Teribele , Greggio Samuel , Lazzarotto Gabriela , Vidor Pedro , Kunach Peter , Green Kim N. , da Costa Jaderson Costa , Souza Diogo O. , Rosa‐Neto Pedro , Zimmer Eduardo R. , AD MODEL
Published: January 2025

Background

Recent studies have suggested a transient glucose hypermetabolism in early phases of Alzheimer’s Disease (AD), which is followed by a characteristic glucose hypometabolism in dementia stages. This phenomenon desveres further investigation and it is suggested to be associated to glial/inflammatory or compensatory neuronal responses. Here, we aimed to longitudinally investigate brain glucose metabolism in an AD animal model and explore associated cellular and inflammatory changes.

Method

Longitudinal assessments, including cerebral glucose metabolism (18F]FDG‐PET), behavioral tasks and cerebrospinal fluid (CSF) sample collection were performed at 3, 6, 9, and 12 months of age (mo) in wild type (WT) and TgF344‐AD rats (Tg). Glial and inflammatory markers were evaluated in the CSF via ELISA multiplex. A cross‐sectional cohort was used to follow the spatial distribution of Aβ plaques (IHC), to assess the brain content of glial and neuronal proteins (western blot), and to analyze the cortical glutamate uptake (ex‐vivo slices) at the same time points.

Result

At 9mo, three months after the initial appearance of Aβ plaque deposits, Tg animals exhibited cortical glucose hypermetabolism (Figure 1A‐C). At the same age, astrocytic glutamate uptake was increased in the cortex and hippocampus (Figure 2). Declines in performance on the Y‐maze and Novel Object Recognition tasks were observed at 9 and 12mo (Figure 1D). CSF analysis revealed elevated GFAP levels at 6, 9 and 12mo, and reduced S100B at 9mo (Figure 1E e F). Tissue GFAP immunocontent increased in the temporoparietal cortex at 6 and 9mo, in the hippocampus at 9mo, and was reduced in the frontal and temporoparietal cortices at 12mo (Figure 3).

Conclusion

Our findings suggest the presence of an early, transient phase of brain glucose hypermetabolism in TgF344‐AD rats, consistent with observations in recent animal and human studies. This phenomenon seems to be closely linked to the astrocyte response, reflected in variations of crucial astrocyte proteins such as GFAP and S100B, along with an increase in the glutamate uptake by these cells. In contrast, neuronal, microglial and inflammatory markers did not exhibit changes during this timeframe.
Using Remote, Automated Verbal Paired Associates for Learning Over Repeated Exposure: Six Learning Bursts Over Six Months
Authors: Kaula Alexander J , McCoy Bronagh , Taptiklis Nick , Cormack Francesca K
Published: January 2025

Background

Learning over repeated exposures (LORE) is an emerging paradigm that has shown sensitivity to AD biomarkers in apparently cognitively unimpaired (CU) samples using visual stimuli. We present results of a six‐month study in a CU sample that explored brief (<2 minute) assessment of verbal LORE alongside other measures of memory and sleep.

Method

The Prolific platform was used to recruit 190 participants. In a baseline session we obtained a measure of sleepiness (Karolinska Sleepiness Scale), and visual and verbal measures of memory using paired associates learning (PAL) and verbal paired associates (VPA). Five‐day bursts of VPA‐LORE were then carried out once‐monthly for six months, with participants learning a new set of word‐pairs each burst. One month after the final burst, delayed recall for all 48 associates was tested in a single session.

The first session of a burst comprised presentation of the month’s associates, followed by a test of immediate recall. In subsequent sessions, cued‐recall was tested first, after which the set was presented again. A measure of LORE was created by integrating recall scores over the burst. We used linear mixed‐effects modelling to explore relationships among 1) age and baseline memory measures, measures of immediate recall and LORE and 2) between day‐by‐day scores, age and sleepiness.

Result

Test‐retest correlations of LORE scores from burst‐to‐burst over the six bursts were strong (rp = .69 ‐ .75). At baseline, sleepiness did not affect PAL‐errors or VPA‐errors. PAL‐errors were positively associated with age (β = 0.391, p<.001) and VPA‐errors, but VPA‐errors were not associated with age. LORE scores were not significantly associated with age or PAL‐errors. However, day‐to‐day learning within a burst was impacted by daily sleepiness (β = ‐0.122, p<.001). In contrast to LORE, delayed‐recall after the final burst was significantly impacted by age (β = ‐0.010, p = .043).

Conclusion

Reliability of VPA‐LORE was found to be good between bursts over six months. The association of LORE with PAL but not with age suggests VPA‐LORE measures a stable form of memory different from PAL. Additionally, the sensitivity the task to sleepiness may be relevant for use in AD‐related research given the impact of AD pathology on sleep.
Genome‐Wide Association Studies of Cognitive Progression in Alzheimer’s Disease
Authors: Shi Ruyu , Fan Kang‐Hsien , Lopez Oscar L. , Feingold Eleanor , Liu Menghan , Gorijala Priyanka , Cruchaga Carlos , Kamboh M. Ilyas
Published: January 2025

Background

Cognitive decline represents a significant and gradual clinical manifestation in individuals affected by Alzheimer’s disease (AD). Currently, there is a lack of effective treatments to delay its progression. Quantitative genome‐wide association studies (GWAS) have yielded limited insights into progression traits. The primary objective of this study was to identify underlying genetic variants in AD patients using longitudinal Mini‐Mental State Examination (MMSE) measures.

Method

A total of 1,089 AD patients, including 410 with available whole genome‐sequencing (WGS) data from the University of Pittsburgh Alzheimer’s Disease Research Center (ADRC), and 1,117 AD patients from the Washington University in St. Louis were recruited and genotyped. GWAS were executed on four MMSE‐based cognitive decline phenotypes. Subsequently, a meta‐analysis was performed, followed by a functional exploratory analysis of identified top variants.

Result

Distinct genetic variants were associated with each progression phenotype. Notably, a genome‐wide significant association was identified on chromosome 4 near the TAPT1 (top SNP = rs79296051; MAF = 0.017; p = 3.47E‐08; z = ‐5.52) gene, linked explicitly to the annual MMSE percentage changes. Additionally, several suggestive associations (p < 1E‐05) were observed in the other decline phenotypes.

Conclusion

We identified one genome‐wide significant association and multiple suggestive associations with MMSE‐based cognitive progression in AD patients. Replications of these results in independent larger cohorts are needed.
Characterization of writing in patients with the semantic variant of Primary Progressive Aphasia
Authors: Machado Thais Helena , Pereira Rafaela Souza , Campanha Aline Carvalho , de Araujo Caroline Martins , Carthery‐Goulart Maria Teresa , de Paula França Resende Elisa , de Souza Leonardo Cruz , Caramelli Paulo
Published: January 2025

Background

Language impairment manifestations in patients with the semantic variant of primary progressive aphasia (S‐PPA) include surface dysgraphia. Word and pseudoword dictation helps characterize errors in these patients’ writing to better conduct their therapeutic strategies. Few studies have addressed written language in patients with dementia, and even fewer have done so in PPA. The objective was to analyze, classify, and quantify the types of writing errors in adults with S‐PPA using word and pseudoword dictation.

Methods

This cross‐sectional study was conducted in a Cognitive and Behavioral Neurology Outpatient Clinic. Its project was approved by the Research Ethics Committee. The research analyzed 19 patients with S‐PPA and 30 healthy individuals using a word and pseudoword dictation protocol. The two groups were matched for age, sex, and education level. The inclusion criteria for the control group were subjects whose Mini‐Mental State Examination score was appropriate to their age and education level, without any neurological and/or psychiatric diseases, and not taking medications that interfere with cognition. For the patients’ group, they were only required to be medically diagnosed with S‐PPA. Descriptive statistical analysis was performed, showing data frequency.

Results

The S‐PPA group performed worse than controls on the word and pseudoword writing task. Both groups performed worse in irregular words and grapheme substitution.

Conclusion

Patients with S‐PPA performed worse in word and pseudoword writing than controls, most often in grapheme substitution and irregular words, which can be explained by the frequent occurrence of surface dysgraphia present in S‐PPA, which hinders their access to the lexical route.
Differential Effects of Anticholinergic Medications in Patient hiPSC‐Derived Neurons
Authors: Schwarze‐Taufiq Tiara A. , Pranoto Inez , Hui Katherine , Ogg Jordan , Zhu Ruowei , Crane Paul K. , Gray Shelly L , Young Jessica E.
Published: January 2025

Background

Anticholinergic (AC) use remains common in older adults despite evidence of safety risks, including dementia risk. Evidence from population studies suggests that dementia risk may vary by AC class. This variation might be explained by confounding by indication. In vitro models, using human neural cells where cells are directly experimentally exposed to a drug and phenotypic outcomes are measured, may address this issue. We identified classes of AC medications with and without an association with dementia based on population studies. We treated human induced pluripotent stem cell‐derived neurons (hiPSC‐Ns) with each AC medication and performed cellular assays to examine the effects on AD phenotypes.

Method

We have generated hiPSC lines from participants in the Adult Changes in Thought Study (ACT), a longitudinal study in Seattle, WA. We differentiated hiPSC‐Ns from ACT cell lines using protocols in our laboratory. We treated neurons with different classes of AC medications: antidepressants (amitriptyline, doxepin, paroxetine), antihistamines (diphenhydramine, chlorpheniramine), bladder antimuscarinics (oxybutynin, tolterodine), and antispasmodics (atropine). As a control, we treated cells with the classic cholinergic compound carbachol. Cells were treated with two drug doses (10 uM, 50 uM) at two time points (24 hours, 48 hours). We used molecular assays to test AD‐associated cellular outcomes (neurotoxicity, synaptic gene expression and Amyloid beta [Aβ]).

Result

We document differential effects of medications on cytotoxicity, secreted Aβ levels, and synaptic gene expression. Several drugs demonstrated dose‐dependent (doxepin, oxybutynin, paroxetine, amitriptyline) and/or time dependent (oxybutynin, paroxetine) neurotoxicity. We also observed differential effects on Aβ secretion. Oxybutynin, a bladder antimuscarinic, consistently induced an increase in the Aβ42/40 ratio, largely driven by increased secreted Aβ42. Further, all antidepressants and bladder antimuscarinics tested increased the secreted Aβ42/40 ratio at 50 uM. These findings are consistent across lines of different genetic backgrounds.

Conclusion

Stem cell‐derived neuronal models provide a useful strategy to complement pharmacoepidemiological studies to help distinguish molecular pathways versus confounding by indication of drugs associated with dementia risk. Preliminary results suggest that different AC medications have differential effects on AD‐associated cellular outcomes that are consistent across hiPSC‐Ns derived from individuals with various genetic backgrounds, indicating a molecular effect of the drug.
Characterization bacterial metabolites and peripheral immune cell populations in stable and progressive Alzheimer’s disease
Authors: Loew Ethan B , Tracy Matthew , Jo Cynthia , McCormick Beth , Haran John P
Published: January 2025

Background

Alzheimer’s disease (AD) is the most common type of dementia which results in debilitating memory loss as the disease advances. However, among older adults with AD, some may experience rapid cognitive decline while others may maintain a stable cognitive status for years. In addition to the amyloid plaques, tau tangles, and neuronal inflammation characteristic of AD, there is strong evidence of dysregulation in the peripheral immune system, including decreased naïve T cells and increased memory T cells among older adults with AD. It is currently unknown what underlies dysfunction in the peripheral immune system or whether changes in peripheral immune cells are associated with cognitive decline.

Method

We have performed unbiased metabolomics and characterized stool metabolites present in 35 AD versus 35 propensity matched healthy controls. In our ongoing work, we are longitudinally characterizing resting peripheral immune cell populations by flow cytometry and gut microbiome composition by metagenomic sequencing.

Result

We have identified an increase in the metabolites methionine sulfone (1.46 fold, p<0.05), homocysteine (1.67 fold, p<0.05), and cysteine (1.33 fold, p<0.05) in the stool of older adults with AD compared to controls. Among the population of AD patients experiencing cognitive decline, determined by increasing ADAS‐Cog score >6 points over one year (n = 7 declining vs n = 8 stable cognition), we have identified increases in the bacterial genes responsible for methionine production at the point of cognitive decline compared to previous timepoints and between patients with decline versus stable cognition. In accordance with the role of methionine in promoting immune cell proliferation and differentiation, we have compared the composition of peripheral immune cells among adults with declining versus stable cognition and identified a decrease in CD4+/CD62L+ naïve T cells (percent of CD4+ lymphocytes, stable 0.3055 vs declining 0.0955, p = 0.0042) and increased effector memory CD4+ T cells (percent of CD4+ lymphocytes, stable = 0.2375 vs declining = 0.4164, p = 0.0225).

Conclusion

This longitudinal clinical study identifies changes in stool metabolites and resting peripheral T cell populations in AD patients and among AD patients with cognitive decline. We propose that gut bacterial produced methionine acts to promote peripheral immune differentiation and dysfunction, leading to cognitive decline in AD.
Automated Neurofibrillary tangle detections in digital histopathology sections of the brain
Authors: Arezoumandan Sanaz , Teunissen‐Bermeo Eric , Capp Noah , Zablah Jamila , Ohm Daniel T , Phillips Jeffrey S , McMillan Corey T , Lee Eddie B , Wolk David A , Yushkevich Paul A. , Irwin David J
Published: January 2025

Background

Alzheimer’s disease (AD) is the most common neurodegenerative disease, and it is characterized by aggregation of misfolded proteins in the brain. Intraneuronal accumulation of tau pathology form neurofibrillary tangles (NFT) in AD. The assessment of the severity of intraneuronal inclusions holds significance in studying the clinicopathological associations in neurodegenerative diseases. Using machine learning methods, we have developed an automated tool to detect NFTs in immunohistochemically stained sections.

Method

We trained a weakly supervised machine learning algorithm called WildCat to classify inclusions in AT8‐stained 6µm sections of the hippocampus and locate areas with high probability of NFTs in the tissue. Next, we utilized the WildCat activation outputs and improved the NFT detections by thresholding and applying morphological filters. Finally, in order to validate our methods, we generated a validation dataset using QuPath software by manually annotating NFTs (N = 600) in 175 × 175µm regions of interest (N = 103). We then tested the correlation between manual and automated measurements to validate our method (Fig. 1).

Result

The WildCat classification model showed outstanding performance by accurately distinguishing NFTs from non‐tangle inclusions, achieving high accuracy (97.31%), recall (99.37%), and precision (99.3%). In addition, we tested the correlation between final output of our model with manual measurements of tangles in our validation dataset, where we found strong correlations in tangle counts and tangle percent area‐occupied between the two methods (R = 0.84‐0.88, p<0.001) (Fig. 1).

Conclusion

Automated tools can reliably generate measurements of NFT density in AD tissue sections. Moreover, this method can be applied to other types of pathologies and may offer a helpful tool for the study of other neurodegenerative diseases.