bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large‐scale discovery of novel shared genetic etiology between stroke and neurodegenerative diseases like Dementia, Multiple sclerosis, Parkinson’s Disease, Amyotrophic Lateral Sclerosis
Authors: Khamkar Akhilesh Shailendra , Chauhan Ganesh 
Published: January 2025

AbstractBackgroundStroke, a cerebrovascular condition, and neurodegenerative diseases (ND) like Dementia, Multiple sclerosis, Parkinson’s Disease, Amyotrophic Lateral Sclerosis are major types of neurological disorders, which are associated with increasing global morbidity and mortality burden. But to what extent shared genetic architecture is involved between stroke and ND is unknown.MethodWe investigated shared genetics between stroke (10 subtypes) and ND (6 diseases) using large scale Genome‐Wide Association Study (GWAS) summary statistics data for Cross‐Ancestry, European and South Asian samples including Indians. We used largest GWAS results for AD from EADB and for stroke subtypes from GIGASTROKE consortium. Different computational approaches ‐ LDSC, PLACO, COLOC was used to assess genetic overlap between stroke and ND. Functional annotation and gene‐set enrichment analysis (FUMA) was executed to identify genes and molecular pathways to get detailed insight into shared disease mechanisms between stroke and ND. We performed genetic risk score (GRS) analysis to estimate combined effect of stroke associated genetic variants on ND.ResultWe found negative genetic correlation between Alzheimer’s disease and stroke subtypes (all, ischemic & cardioembolic) at genome‐wide level (correlation coefficient (rg): ‐0.12 to ‐0.26, P value: 0.028 to 0.038) (Table‐1). 23 genetic variations showed association with ND (Alzheimer’s disease, Multiple sclerosis) and stroke subtypes (lacunar, ischemic) at genome‐wide significance level (P<5 × 10‐8). We found 184 causal lead pleiotropic SNPs for stroke‐ND trait pairs (Figure‐1). Biological pathway analysis shows that shared genes are highly enriched in pathways related to immune system, protein catabolism, phagocytosis. Genetic risk scores of stroke subtypes for South Asians including Indian samples shows association with neurodegenerative diseases (beta: ‐0.005 to 0.003, P value: 2.23 × 10‐8 to 0.021) (Table‐2).ConclusionThis is first study which shows extensive pleiotropy present between stroke and neurodegenerative diseases at genome‐wide level. We found GRS of stroke subtypes for South Asian samples also associated with neurodegenerative diseases which suggest that applicability of GIGASTROKE GWAS data of Indians in prediction of neurodegenerative diseases; despite smaller sample size compared to other ancestries in world. These research findings have strong implication for future development of early diagnosis, prevention and treatment strategies for both cerebrovascular and neurodegenerative diseases.
Brain Connectome Graphs based Machine Learning for Diagnosis of Alzheimer’s Disease
Authors: CHEN Ke , Weng Ying , Dening Tom , Hosseini Akram A. , Zuo Guokun 
Published: January 2025

AbstractBackgroundAlzheimer’s Disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline and memory loss. Early and accurate diagnosis of AD is crucial for patient information, advance planning, and potentially effective intervention and treatment. The integration of machine learning techniques with brain connectome graphs, encompassing both structural and functional brain connectomes, can enhance the accuracy and efficiency of AD diagnosis.MethodWe propose a framework for AD diagnosis using both structural and functional brain connectome graphs with machine learning techniques. Our framework comprises three stages: image pre‐processing, brain connectome graph construction, and machine learning‐based AD diagnosis. We use PANDA and fMRIPrep for image pre‐processing and brain connectome graph construction. The two types of derived graphs, namely brain structural and functional connectome graphs, are then used as joint inputs for graph neural network (GNN)‐based models for AD prediction, including its early stage, and mild cognitive impairment (MCI).ResultThe experiments are performed on diffusion magnetic resonance imaging (dMRI) and functional MRI (fMRI) obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) datasets, displaying promising results with high performance in identifying AD, (MCI), and cognitively normal (CN) patients. Explainable artificial intelligence algorithms are also applied to the model’s predictions for visualizing decision strategies.ConclusionThe findings of our research contribute to the burgeoning field of neuroinformatics by offering a novel and effective approach to AD diagnosis. The integration of machine learning with brain connectome graphs has potential to provide early and accurate identification of individuals at risk of AD, and pave the way for timely interventions and personalized treatment strategies. Moreover, this study sheds light on the intricate connectome‐level changes associated with AD and fosters a deeper understanding of the disease’s pathophysiology. Ultimately, this research has established a significant step towards leveraging advanced computational techniques to enhance our ability to diagnose and manage AD.
A novel coumarin derivative treatment ameliorates neuroinflammation and cognitive functions in the ICV‐STZ‐induced rat model of Alzheimer’s disease
Authors: SHARMA PRAJJWAL 
Published: January 2025

AbstractBackgroundNeuroinflammation has gained substantial attention for its involvement in the progression of Alzheimer’s disease (AD).MethodRecently, it was discovered that platelets, which make up 90% of the circulatory Aβ, encourage the development of AD. Therefore, we hypothesized to use a novel coumarin derivative PS21HKR, which is believed to possess anti‐platelet and anti‐inflammatory properties for the treatment of AD. We investigated the effects of PS21HKR on STZ induced cognitive decline and neuroinflammation. Intra‐cerebroventricular streptozotocin (ICV‐STZ) (3mg/Kg) induced Wistar rat models of AD were used in the study. Rats were divided into 3 groups including sham, STZ and PS21HKR group.ResultBehavioural studies revealed that PS21HKR mitigates the cognitive deficit associated with STZ. Anti‐platelet effect of PS21HKR was confirmed by tail vein bleeding assay. Further, in‐vitro studies were performed on BV2 cells including the MTT assay and determination of expression of inflammatory markers. The results suggested that PS21HKR potentially regulated the expression of pro‐ and anti‐inflammatory cytokines.ConclusionTherefore, findings of this study indicate that PS21HKR has a potent neuroprotective effect by virtue of its anti‐platelet and anti‐inflammatory activity.
Anti‐saccadic task can distinguish between patients at risk of developing Alzheimer’s disease and cognitively unimpaired patients in a memory clinic
Authors: Ištvánfyová Zuzana Wallin , Nilsson Mattias , Hagman Göran , Kivipelto Miia 
Published: January 2025

AbstractBackgroundEarly detection is crucial for alleviating Alzheimer’s disease (AD) burden. At present, assessment for early detection of AD is time‐consuming, costly, and often invasive. In recent years, various eye‐tracking methodologies have emerged, and they show promising results in detecting persons at risk of developing AD dementia (ADD). This study aims at identifying suitable anti‐saccadic measures to detect people with early AD.MethodPreliminary data from 21 cognitively impaired and 45 cognitively unimpaired individuals was collected from a memory clinic (Karolinska University Hospital, Sweden). The data included results from an anti‐saccadic task, neuropsychological tests battery, demographic information, cerebrospinal fluid markers (CSF), and AI‐computed volumetry from magnetic resonance imaging. Median values were calculated on anti‐saccadic measures with the strongest associations to cognition, CSF, and volumetry. The identified measures were proportion of errors (PoE) and latency of a correction saccade (LoCS). Subsequently, the clusters of high and low performers were compared using the Mann‐Whitney U test.ResultBoth PoE and LoCS were able to distinguish between high and low atrophy grade in all cortical brain regions with the highest effect size found in the right cerebral lobe for PoE (U = 266.00, d = 1.36, p < .001) and the right parietal lobe for LoCS (U = 227.50, d = 1.234, p < .002). PoE and LoCS could also distinguish between high and low cognitive function, with the highest effect size for LoCS in verbal delayed recall (U = 210.50, d = 1.061, p < .001) and visual immediate recall (U = 217.00, d = 1.027, p < .001). We did not find any significant differences in the CSF between the clusters.ConclusionA brief anti‐saccadic task was able to distinguish between individuals with and without brain atrophies, with PoE capturing atrophy grade with largest effect size. Similarly, the task distinguished individuals with better and worse cognition, with LoCS resulting in largest effect sizes. Our results indicate that both PoE and LoCS have a potential to distinguish individuals at risk of ADD from cognitively unimpaired individuals. Furthermore, the lack of CSF association raises questions about chronology of pathological processes involved in AD.
Lithium as a pharmacological approach to treat behavioral complications in Alzheimer’s disease: a preclinical study
Authors: Singulani Monique Patricio , Camarini Rosana , Talib Leda Leme , Britto Luiz Roberto , Forlenza Orestes Vicente 
Published: January 2025

AbstractBackgroundNearly all individuals with Alzheimer’s disease (AD) develop neuropsychiatric symptoms (NPS). Lithium is a mood‐stabilizer and is efficient in reducing disruptive behaviors in bipolar‐disorder; this characteristic could be an opportunity to investigate the use of lithium in treating behavioral changes in AD.MethodWe tested lithium carbonate treatment in 3xTg‐AD and age‐matched Wild‐type male mice (CEUA/PROCESS: 1605/2020; 4127240122). The drug was administered ad libitum via lithium‐supplemented chow (1.0g Li2CO3/kg of chow; 12‐weeks) from 9‐ to 12‐month‐old. Two behavioral test batteries were performed: (1) open‐field test (OFT), novel‐object recognition test (NORT), elevated zero‐maze test (EZMT), and rotarod test; (2) tail‐suspension test (TST), forced‐swim test (FST), and sucrose preference test (SPT). Immunohistochemistry method was performed to analyze amyloid‐β (Aβ) accumulation (6E10) in areas of the brain. Statistical analysis was performed using two‐way ANOVA followed by Bonferroni post‐hoc test and unpaired t‐test (IBM_SPSS Statistics® software 23). We considered statistically significant p<0.05.ResultOur results demonstrated that lithium had a significant rescue/prevention effect on anxiety‐ and depression‐related behaviors in AD. In both OFT (F(1, 28) = 37.15; p<0.001) and EZMT (F(1, 28) = 19.44; p<0.001), a suppression in anxiety‐related responses was detected in 3xTg‐AD+Lithium mice versus 3xTg‐AD. Similar results were found in TST (F(1, 28) = 11.70; p<0.01) and FST (F(1, 28) = 7.96; p<0.01) with reduction of depressive‐related behavior. In SPT (F(1, 24) = 17.86; p<0.001), 3xTg‐AD+Lithium mice presented an increase in sucrose preference versus 3xTg‐AD, suggesting benefice effects of lithium on anhedonia signs detected in AD. In NORT, 3xTg‐AD+Lithium mice demonstrated greater index in recognition memory parameter versus 3xTg‐AD, suggesting prevention of short‐ (F(1, 28) = 8.37; p<0.01) and long‐term memory (F(1, 28) = 7.99; p<0.01) in AD. We also reported reduction of nearly 50% in Aβ immunoreactivity in areas such as parietal cortex (F(1, 21) = 571.90; p<0.001), CA1 (F(1, 20) = 357.28; p<0.001), dentate gyrus (F(1, 20) = 417.74; p<0.001), subiculum (F(1, 20) = 7073.19; p<0.001), entorhinal cortex (F(1, 21) = 1562.86; p<0.001), and amygdala (F(1, 22) = 419.79; p<0.001), in 3xTg‐AD+Lithium mice versus 3xtg‐AD; suggesting the neuroprotective action of lithium, which partially explains the positive cognitive and non‐cognitive behavioral changes observed with chronic lithium treatment.ConclusionThe efficacy of a low‐dose lithium treatment in improving cognitive loss and NPS suggest it as therapeutic potential to treat AD.
Enhancing Single‐Domain Antibody‐Based Protein Degradation for Synucleinopathies
Authors: Jiang Yixiang 
Published: January 2025

AbstractBackgroundSynucleinopathies lack cures. Antibody therapies targeting α‐synuclein aim to inhibit aggregation and enhance degradation, but have limited brain entry because of size (150kDa). Smaller single‐domain antibodies (sdAbs, 15kDa) have substantially improved brain uptake. Previously, we developed sdAb‐based probes (2D10 and 2D8) enabling specific α‐synuclein imaging in mice post i.v. injection, correlating with lesion burden, indicating therapeutic and diagnostic potential (Jiang Y et al Sci Adv 2023).MethodTo enhance sdAbs’ efficacy, we developed 2D8‐PEGn‐T (n = 2,4,6), linking 2D8 sdAb and thalidomide (T) with different PEG linkers to promote proteasomal degradation (sdAb‐PROTAC). We assessed sdAb binding affinity to α‐synuclein preparations by biolayer interferometry, examined α‐synuclein degradation in M83‐mouse primary culture, and evaluated therapeutic efficacy in M83‐synucleinopathy mouse model (n = 17). Using 2D10 sdAb linked to a near‐infrared‐tag and In‐Vivo‐Imaging‐System, we assessed brain α‐synuclein burden pre‐treatment. Mice with similar burden received 3 i.v. sdAb injections (molar equivalent: 100 µg of 2D8) 3 days apart, with re‐imaging after 3 days, followed by brain extraction for analyses of α‐synuclein clearance and potential toxicity.Result2D8‐PEGn‐T’s affinity after conjugation was comparable to 2D8’s affinity. 2D8‐PEG4‐T targeted α‐synuclein and Cereblon, inducing ubiquitination and proteasomal degradation. In the culture, 2D8‐PEG4‐T prevented α‐synuclein‐induced toxicity and reduced α‐synuclein levels via lysosomal‐ and proteasomal‐pathways, outperforming unmodified 2D8 sdAb that mainly cleared α‐synuclein via the lysosomal‐pathway. In the M83‐synucleinopathy mouse model, 2D8‐PEG4‐T significantly (81%, p = 0.0049) reduced α‐synuclein brain signal, surpassing 32% for 2D8 (p = 0.3195) vs PBS control. Western blots showed 2D8‐PEG4‐T to be more efficacious (89‐93% reduction, p<0.0001) in reducing insoluble total and pS129 α‐synuclein, compared to 2D8 (59‐69% reduction, p = 0.0015 and 0.0016) vs PBS control. Additionally, 2D8‐PEG4‐T decreased soluble total and pS129 α‐synuclein levels by 70% (p = 0.0072) and 90% (p = 0.0001), surpassing 2D8 that did not significantly reduce soluble total (p = 0.8643) or pS129 α‐synuclein (reduced by 34%, p = 0.1018), compared to PBS control.Conclusion2D8‐PEG4‐T enhances α‐synuclein proteasomal degradation while maintaining 2D8’s lysosomal clearance. Its superior α‐synuclein clearance, compared to unmodified 2D8 sdAb in vitro and in vivo, highlights its therapeutic potential for synucleinopathies. Small sdAbs with improved brain entry and potency may enhance clinical benefits in antibody‐based therapies.
Leveraging dynamic enhancer landscapes to decode microglia phenotypes in Alzheimer’s disease
Authors: Glass Christopher K. 
Published: January 2025

AbstractBackgroundMicroglia are the major innate immune cells of the brain and play diverse roles in brain development and homeostasis. In the context of Alzheimer’s disease, microglia acquire new phenotypes that can exert protective or pathogenic roles. Single cell and single nuclei RNA sequencing experiments have defined molecular signatures of different disease‐associated microglia states associated with protective or pathogenic functions, but the mechanisms driving these transitions are not known. As a general approach to this question, we are performing a quantitative analysis of the epigenetic landscapes of mouse and human microglia subsets in models of amyloid pathology.MethodIn collaboration with the Butovsky and Henna laboratories, we defined amyloid responsive enhancers in aged APP/PS1 mice using ATAC seq. In collaboration with the Blurton‐Jones laboratory, we used ATAC‐seq to perform quantitative analysis of enhancers in homeostatic, MHCII‐high and CD9‐high human microglia engrafted into humanized 5XFAD mice. We integrated these findings with patterns of transcription factor expression and changes in gene expression.ResultThe responses of both mouse and human microglia to amyloid pathology in vivo was associated with significant increases in ATAC‐seq signal at more than 1400 genomic locations. A large fraction of these locations correspond to putative enhancers. More than ten distinct transcription factor motifs were identified in both mouse and human amyloid responsive ATAC‐seq peaks. There was a near complete overlap of these motifs in both mouse and human microglia, which were associated with a similar set of expressed transcription factors. A subset of these factors was evaluated for their potential roles in regulating amyloid responsive genes using human iPSC derived microglia and mouse macrophage systems. Although the transcription factor motifs identified in amyloid responsive ATAC‐seq peaks were nearly identical between mouse and human microglia, there was substantial divergence in the downstream genes they regulated.ConclusionThese studies indicate that the response to amyloid involves many transcription factors, nominates specific factors for further study, and reinforces the value of engrafting human microglia into disease models as a means of investigating the impact of human‐specific non coding regulatory elements.
Epigenetic signatures of genetic risk in Alzheimer’s disease
Authors: Marzi Sarah 
Published: January 2025

AbstractBackgroundMicroglia are key players in Alzheimer’s disease (AD): Genetic risk for AD is enriched in microglial enhancers, and microglial gene regulatory networks have been shown to be disrupted in AD. Here, we studied polygenic and variant‐specific (APOE) risk burden for AD in a xenotransplantation model of AD and human post‐mortem brain tissue.MethodWe profiled gene regulation by RNA‐seq and ATAC‐seq in human iPS‐derived microglia, xenotransplanted into the APPNL‐G‐F mouse model of AD. We used isogenic APOE2/3/4 and APOE knockout (KO) microglia. In parallel, we purified microglial nuclei from a large cohort of human post‐mortem brain samples with and without AD neuropathology. We performed nanobody H3K27ac CUT&Tag on these nuclei to characterize the AD‐associated microglial enhancer landscape.ResultWe observe numerous gene regulatory differences across APOE microglia in the chimeric mice. From E2 to E3 and E4 we see increased expression and regulation of pro‐inflammatory cytokine signalling. Conversely, the potentially protective disease associated and antigen‐presenting response microglia states are downregulated. Human post‐mortem microglia show widespread AD‐associated acetylation differences. By leveraging genetic variants in the CUT&Tag sequencing data, we were able to directly link genetic variants and epigenetic signatures, identifying potential mechanisms underlying non‐coding genetic risk. Finally, we show parallels between APOE‐linked epigenetic responses in human post‐mortem samples and the xenotransplantation model.ConclusionWe identified gene regulatory mechanisms underlying microglial activation in neuropathological environments in chimeric mice and human post‐mortem brain samples. Our findings are important for understanding the upstream epigenetic mechanisms governing microglial activation in neurodegenerative disease, as well as directly linking these to genetic risk factors of disease.
Unraveling temporal transcription dynamics of molecular FTD and ALS subtypes
Authors: Shen Ting , Spencer Barbara E , Van Deerlin Vivianna M , Phatnani Hemali , Lee Eddie B , McMillan Corey T , Consortium NYGC ALS 
Published: January 2025

AbstractBackgroundFrontotemporal degeneration (FTD) and amyotrophic lateral sclerosis (ALS) constitute a clinicopathologic spectrum with multifaceted heterogeneities. Brain transcriptomics may help to identify molecular subtypes of FTD and/or ALS but this testing is only possible at autopsy and thus is cross‐sectional and representative of end‐stage disease. Subtype and Stage Inference (SuStaIn) is an unsupervised machine‐learning algorithm that was employed to identify temporal dynamics of data‐driven subtypes of ALS and FTD.MethodWe utilized transcriptomic RNA‐seq data from frontal cortex tissue provided by the NYGC ALS Consortium including individuals with FTD (n = 27), ALS (n = 118), ALS‐FTD (n = 23), and non‐neurological controls (n = 42). After quality control, 19,817 genes were adjusted for age, sex, RIN, contributing site, and cell‐type proportion. Weighted gene co‐expression network analysis (WGCNA) constructed co‐expression modules and the module eigengene of each module was compared between FTD‐ALS and controls. The significantly up‐regulated or down‐regulated modules underwent functional enrichment analyses for biological annotations. We then utilized the gene expression profiles of significant modules to train the SuStaIn model to identify molecular subtypes with distinct gene expression trajectories.ResultWGCNA identified 16 modules, of which 9 were differentially expressed in case‐control comparisons with functional enrichment in pathways such as “neuronal system”, “nucleic acid metabolism”, “protein biosynthesis and metabolism”, “immune system”, and “mitochondrion” (Fig. 1). The SuStaIn model identified three novel molecular subtypes (Fig. 2): one had early evidence of altered gene expression in “protein biosynthesis and metabolism” and “mitochondrion” (ProteoMetabolic/Mitochondrial subtype); another initially involved pathways related to “neuronal system”, and “nucleic acid metabolism” (Neuronal/NucleoMetabolic subtype); and one subtype had initial involvement of “immune system” (Immune subtype). The ProteoMetabolic/Mitochondrial and Neuronal/NucleoMetabolic subtypes had lower frequencies of ALS compared to the Immune subtype which had a lower frequency of FTD and ALS‐FTD. Moreover, the Immune subtype exhibited a higher frequency of bulbar‐onset and lower frequency of cognitive‐onset than the other two subtypes.ConclusionOur results revealed three data‐driven molecular subtypes within the FTD‐ALS spectrum with distinct patterns of early gene pathway involvement. This may contribute to further understanding of potential molecular mechanisms driving some of the heterogeneity and provides the first application of SuStaIn in identifying temporal dynamics of brain transcriptomics.