bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of the therapeutic modulation of APT20TTMG on U1 snRNP complex assembly in Alzheimer’s disease
Authors: Bottos Rafael , Zimmer Camila , Sinatti Vanessa , Soares Ericks , Rafii Michael , Buee Luc , Leal Caio 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is the most common cause of dementia worldwide. It is characterized by dysfunction in the U1 small nuclear ribonucleoproteins (snRNPs) complex, which may precede TAU aggregation, enhancing premature polyadenylation, spliceosome dysfunction, and causing cell cycle reentry and death. Thus, we evaluated the effects of a synthetic single‐stranded cDNA, called APT20TTMG, in induced pluripotent stem cells (iPSC) derived neurons from healthy and AD donors and in the Senescence Accelerated Mouse‐Prone 8 (SAMP8) model.MethodFollowing a 7‐day treatment with 5 concentrations of APT20TTMG in iPSC‐derived healthy and AD neurons, mitochondrial activity, glutamate release, and TAU levels were analyzed. The most effective concentration was chosen for the analysis of RNA‐seq differential expression and 3’ untranslated region and coding sequence (UTR/CDS) expression ratios for U1‐70K, SNRP200, MAPT, and APP genes. Levels of U1‐70K, TAU, Aβ, and GFAP were analyzed in 20‐week‐old female SAMP8 mice (Animal Welfare Act, Austria: BGBl. II Nr. 542/2020, BGBl. I Nr. 76/2020, BGBl. I Nr. 86/2018, BGBl. I Nr. 8/2022), treated with 0.3 µg APT20TTMG infused continuously for 42 days (i.c.v.).ResultIn addition to unaffected mitochondrial activity and glutamate release, treatment decreased TAU in AD neurons, with no changes in healthy neurons. Metabolic pathway enrichment and network analysis identified four prominent clusters containing differentially expressed genes (DEGs) associated with pathways like cell cycle, PI3K‐Akt signaling pathway, fatty acid metabolism, MAPK signaling pathway, and steroid biosynthesis. APT20TTMG also corrected target assembly, avoiding premature polyadenylation of all analyzed genes. In vivo, treatment decreased U1‐70K in both cortex and hippocampus, as well as Aβ in cortex, and insoluble pTau in hippocampus. It also reduced gliosis (GFAP) in the cortex of animals.ConclusionAPT20TTMG specifically decreases TAU protein in AD neurons, with a wide safe effect for human brain cells. Its ability to correct the U1 snRNPs dysfunction prevents premature polyadenylation in key genes and leads to a favorable enrichment of DEGs related to pathways deregulated in AD. It also decreases important hallmarks of the disease, in addition to controlling severe astrogliosis. These data evidence the great potential of utilizing APT20TTMG as a disruptive approach for neuronal protection in AD.
Deep learning‐based estimation of future brain atrophy using baseline MRI and PET
Authors: Le Linh N. N. , Fletcher Evan , Qi Jinyi , Fan Audrey P. 
Published: January 2025

AbstractBackgroundCortical brain atrophy is an excellent marker of clinical decline and can support future clinical course prediction in cognitive impairment. We used a U‐Net image‐generation deep learning network to predict future cortical atrophy rates in elderly populations, with initial T1‐weighted (T1w‐) MRI or baseline amyloid‐PET serving as inputs to the model.MethodMRI and PET data were retrospectively collected from Alzheimer’s Disease Imaging Initiative (ADNI) and all participants had two serial T1w‐MRI scans (Figure 1A,B). The ground truth was an atrophy map (in log‐Jacobian values) generated from Tensor Based Morphometry (TBM) of the two longitudinal MRIs (Figure 1E). A U‐Net architecture was used in this study to predict maps of cortical atrophy. We used mean squared error (MSE) for loss function and five‐fold cross‐validation (Figure 1C,D). The testing set was randomly chosen (n=30). Separate models were trained for T1w‐MRI data as input (T1‐model) and amyloid‐PET as input (PET‐model). The predicted atrophy rate was evaluated across diagnosis groups in the test set using the whole‐brain structural similarity index measure (SSIM) to the TBM ground truth. Each model's average atrophy at selected brain regions was compared with TBM using paired t‐tests.ResultFigure 2 shows average predicted atrophy maps and corresponding error for each diagnosis group. In the whole brain, for cognitively normal (CN) and mild‐cognitive‐impaired (MCI) groups, T1 model (with SSIMs of 0.67±0.07 and 0.64±0.06, respectively) slightly outperformed PET model (with SSIMs of 0.70±0.06 and 0.69±0.06, respectively). In selected regions, especially gray matter, we observed a larger rate of atrophy in Alzheimer’s Disease (AD) compared to MCI and in MCI compared to CN groups in both deep learning models, which was consistent with the ground truth. There was no statistical difference in average atrophy predicted by either model and TBM values for all diagnostic groups in all selected regions, with relatively small absolute error and MSE in both models (Table 1).ConclusionA U‐Net deep learning model trained using only baseline T1 weighted MRI or amyloid PET data could be used to predict future atrophy rates. Both models predicted cortical volume loss and ventricle expansion that differed between AD, MCI, and CN.
Speech characteristics and their association with neuroimaging and CSF biomarkers of AD pathology
Authors: Simpson William , Spilka Michael J , Xu Mengdan , Robin Jessica 
Published: January 2025

AbstractBackgroundDigital speech assessment shows promise as an objective and low burden measure of progressive speech and language changes in AD. While associations with clinical endpoints are well established, less is known about how computational speech features align with biomarkers of AD pathology. The current analysis sought to examine these associations both cross‐sectionally and longitudinally.MethodSpeech samples were collected during a Phase 2/3 clinical trial in mild‐to‐moderate AD. Participants completed clinical assessments at baseline, 3‐month, 6‐month, and 12‐month intervals. Participants completed two picture description speech tasks at each timepoint. Clinical symptoms were assessed using the CDR, ADAS‐cog and MMSE. Biomarkers included neuroimaging markers (cortical thickness and volume) and CSF measurements of tau, p‐tau and AB40/42 ratio. Participants were grouped into terciles for each biomarker and group differences in speech characteristics were assessed. We also explored sensitivity to change by examining whether changes in speech were correlated with changes in biomarker values.ResultIn the cross‐sectional analysis, several speech features showed significant group differences. The strongest associations were for cortical thickness, where average word length, frequency, use of nouns and pronoun:noun ratio showed stepwise differences across biomarker terciles. A similar, stepwise association with biomarker terciles was observed across all three clinical endpoints. Associations with CSF measures were notably weaker, with only 1 significant association (syntactic depth and p‐tau levels). Longitudinally, correlations between cortical thickness and speech characteristics were significant but weaker in magnitude (r<0.2) compared to correlations with clinical endpoints (r>0.4). One modest significant correlation was observed between speech and p‐tau (use of particles, r=‐0.17), while no significant correlations were observed between changes in p‐tau and changes in clinical endpoints.ConclusionWe found converging evidence for stepwise associations between neuroimaging markers and speech features previously shown to track clinical progression in AD. Associations with speech generally appeared weaker than associations with clinical endpoints, consistent with the different level of specificity of each measure (speech vs. general cognition and function). Results highlight a disease‐level association between speech parameters and neuroimaging markers of AD. Future work will help understand how these findings can be leveraged in screening and monitoring settings.
Genetic evidence supports therapeutic hypothesis of increasing progranulin levels for Alzheimer’s Disease
Authors: Robins Chloe , Eicher John , Wang Qin , Liu Jimmy , Liu Dongjing , Richardson Thomas , Davitte Jonathan , Pulford David J. , Gormley Padhraig , Ingelsson Erik D. , Scott Robert A. , Kumar Sanjay , Fang Xu Chun‐ 
Published: January 2025

AbstractBackgroundGenetic variants in GRN, the gene encoding progranulin, are causal for or are associated with the risk of multiple neurodegenerative diseases. Modulating progranulin has been considered as a therapeutic strategy for neurodegenerative diseases including Frontotemporal Dementia (FTD) and Alzheimer’s Disease (AD). Here, we integrated genetics with proteomic data to determine the causal human evidence for the therapeutic benefit of modulating progranulin in AD.MethodUsing AD genome‐wide association studies (GWAS) summary statistics, we performed colocalization and Mendelian randomization (MR) analyses with plasma cis‐pQTL data in UK Biobank and CSF pQTL data from neurodegeneration‐focused cohorts. We additionally performed rare variant analyses using UK Biobank whole genome sequencing data to examine the association of GRN rare variants with AD and dementia. Finally, we characterized common genetic determinants of progranulin levels genome‐wide in UK Biobank.ResultWe observe consistent supporting genetic evidence that increased progranulin levels associate with reduced AD/dementia risk through GWAS (rs5848, OR = 0.93, p = 2.4e‐20), aggregated rare variant associations (p = 9.18e‐14), pQTL colocalization, and MR evidence. Genome‐wide associations with plasma progranulin levels identify several potential modulators (e.g., SORT1, PSAP, APOE), with SORT1 showing the strongest common variant association (p<1e‐300). Given the receptor‐ligand relationship between SORT1 and progranulin, we re‐scaled MR analyses to estimate the therapeutic effect of modulating progranulin with sortilin inhibitors. Our MR analyses suggest that a genetically predicted 2‐fold increase in CSF progranulin levels, as observed in phase 1 clinical trials of a sortilin inhibitor, associates with a ∼46% lower odds of developing AD (OR = 0.54, p = 2.2e‐12).ConclusionOur work demonstrates consistent causal associations of GRN with AD risk. These data provide causal human evidence supporting the potential therapeutic benefits on AD/dementia of inhibiting sortilin to increase progranulin levels.
Examination of GFAP Among a Racial and Ethnically Diverse Community‐Based Cohort: An HABS‐HD Study
Authors: Petersen Melissa , Zhang Fan , Hall James , O'Bryant Sid E. ,   the HABS‐HD Study Team
Published: January 2025

AbstractBackgroundRates of Alzheimer’s disease (AD) Dementia are expected to grow considerably among certain ethnic/racial groups, including Blacks and Hispanics. Glial fibrillary acidic protein (GFAP) has been examined as a biomarker of AD; however, limited research has been conducted examining this particular marker among diverse populations. Therefore, this study sought to address this gap and provide an initial examination among a diverse community‐based cohort.MethodParticipants included n= 326 (n=125 Black; n=26 Hispanic; n=175 non‐Hispanic white) from the Health and Aging Brain Study‐Health Disparities. Clinical information, including age, education, and medical history, was derived via a clinical interview. Cognitive diagnosis of Mild Cognitive Impairment and Dementia were determined by consensus review. Plasma samples were assayed for GFAP using Quanterix kits and run on an HD‐X imager. PET Tau neuroimaging included the 18F‐PI‐2620 tracer. PET Tau positivity was determined based on a clinical read. Statistical analyses were run across racial/ethnic groups and included a correlational analysis between GFAP and PET Tau positivity. Additional analyses included examining the relationship between GFAP, demographic factors, medical comorbidities, and cognitive diagnosis. Statistical significance was set at p<0.05.ResultA significant correlation was found between GFAP and a clinical read of PET Tau positivity only among Blacks (p‐value =0.002). Black participants were also found to have a significant relationship between GFAP and age (p‐value<0.001) as well as a cognitive diagnosis of Dementia (p‐value=0.002). Among non‐Hispanic whites, GFAP was found to be significantly related to age (p‐value=0.03) and a medical diagnosis of Diabetes (p‐value=0.003). No significant findings were found between GFAP and variables such as education, hypertension, dyslipidemia, or a cognitive diagnosis of Mild Cognitive Impairment. There were no significant findings identified among Hispanics.ConclusionThe link between GFAP and select demographic and cognitive factors was found to be greater among Blacks and non‐Hispanic whites; however, findings were likely limited among Hispanics due to the relatively small sample size. Although there was a limited number of participants who were PET Tau positive, the only significant correlation found was among Blacks, highlighting the further need examine such AD biomarkers among diverse populations.
The cross‐sectional association of White Matter Hyperintensities, CAIDE Dementia Risk Score, and cognition in Mexican American elders from the HABS‐HD Study
Authors: Vintimilla Raul 
Published: January 2025

AbstractBackgroundAssociations between CAIDE scores and white matter hyperintensities (WMH) have been reported, and research have shown that both can impact cognition. The cognitive correlates of high CAIDE scores and WMH load in minorities like Mexican Americans (MA) remain unclear.MethodCognitively normal MA from the Health and Aging Brain Study (HABS‐HD) (n = 112), were classified as high or low risk for dementia according to a CAIDE cutoff score of 9. WMH volume was measured from FLAIR using the Statistical Parametric Mapping Lesion Segmentation Tool. After comparing global cognition, memory, executive function (EF), verbal fluency, and processing speed (PS) scores between groups, generalized linear models were used to explore the associations of WMH, CAIDE score and cognition. To better understand the association of WMH and CAIDE score with cognitive performance, we conducted a mediation analysis using PROCESS Macro (Hayes 2013). Age, sex, and education were entered as covariates in the models.ResultParticipants in the high‐risk group were older, less educated, and had lower scores in all cognitive measures. CAIDE score was not associated with any cognitive measures. WMH were associated with memory (B = ‐.14, p <0.001), EF (B = ‐.13, p = .002), and PS (B = .89, p = .02), and the three measures were also associated with the interaction high risk x WMH. In mediation analysis, the regression of WMH on the mediator, CAIDE, was significant (b = ‐.57, p <.001). The analysis showed that the mediator (CAIDE), controlling for WMH, was significant for executive function (b = ‐.09, p <0.001), and processing speed (b = ‐.03, p = .002). The analyses also revealed that, controlling for the mediator (CAIDE), WMH was still a significant predictor of executive function (b = ‐.18, p <0.001), and processing speed (b = ‐.15, p <0.001), but the effects were smaller.ConclusionThese results suggest that MA with higher WMH perform worse in measures of executive function and processing speed, and that association is partially mediated by higher CAIDE scores. Further studies are needed to investigate if cognitive performance in normal individuals with WMH and high CAIDE scores.
Association between plasma angiotensin converting enzyme 1 level and cognition over 12‐years: The Look AHEAD Study
Authors: Yasar Sevil , Anderson Andrea , Hayden Kathleen M. , Espeland Mark A. , Carmichael Owen T. , Clark Jeanne M , Carlson Michelle C , Asby Daniel , Kehoe Patrick Gavin , Miners James Scott 
Published: January 2025

AbstractBackgroundThe renin angiotensin system (RAS) has been proposed as a potential modifier of the development of Alzheimer’s disease (AD). However, prospective studies of RAS are sparse especially among cognitively normal individuals with type 2 diabetes mellitus (T2DM) and other vascular risk factors. We aimed to determine whether plasma levels or activity of the RAS marker ACE‐1 predicts cognitive decline over an 8‐year period in this population.MethodWe performed a secondary data analysis of the Action for Health in Diabetes (Look AHEAD) study among community‐dwelling, non‐demented adults with overweight/obesity and T2DM aged 45‐76 years at baseline observed over a 12‐year period. Of 5,145 participants, we included 310 participants who were not using medications affecting the RAS system, had blood available at years 1, 4 and 10 and had undergone cognitive testing at least once and up to 4 times between years 8 and 16. Plasma ACE‐1 was measured using by ELISA (R&D systems) and ACE‐1 activity using immunocapture fluorogenic peptide assay. Cognitive tests included the Modified Mini‐Mental State Examination (3MSE), the Trail Making Test Parts A and B, the Stroop Color‐Word Test, the Digit Symbol Substitution Test, and the Rey Auditory Verbal Learning (RAVLT) Immediate and Delayed test. A cognitive composite score was derived by averaging standardized cognitive test scores. Mixed effects models were used to relate log converted ACE‐1 levels and activity to performance in cognitive test scores after adjusting for potential confounders.ResultParticipants included in the analyses were more likely to be female (65%), White (76%), and were more likely to have obesity (34%), have lower HgbA1C, LDL and systolic blood pressure control compared to the excluded particpants. Higher mean ACE‐1 levels measured at Y1, 4 and 10 was significantly associated with 3MSE (β=0.1774; p=0.02) and RAVLT‐delayed recall (β=0.1600; p=0.05). The cognitive composite score was not associated with ACE‐1 level. There was no association between ACE‐1 activity and cognitive function.ConclusionIn this sample with T2DM and dementia free at baseline, we observed longitudinal associations between mean ACE‐1 levels and global cognition and memory.
Cerebrospinal Fluid Proteomics in Down Syndrome Identifies Common and Unique Pathological Changes Compared to Late‐Onset and Autosomal Dominant Alzheimer’s Disease
Authors: Bian Shijia , Montoliu‐Gaya Laia , Dammer Eric B. , Sauer Mathias , Alcolea Daniel , Blennow Kaj , Zetterberg Henrik , Fortea Juan , Johnson Erik C.B. 
Published: January 2025

AbstractBackgroundNearly all people with Down Syndrome (DS) develop Alzheimer’s dementia (AD) by the 7th decade of life. However, whether the alterations in fluid biomarker levels associated with DS follow the same pattern to those observed in other forms of AD is not well understood.MethodWe used mass spectrometry‐based proteomics to measure 1116 proteins in cerebrospinal fluid (CSF) across euploid controls (n=130), sporadic late‐onset AD (LOAD, n=89), asymptomatic DS (n=117), prodromal DS (n=57), and dementia DS (n=80) cases, and compared the protein changes observed in DS to those in LOAD and to those recently described in autosomal dominant AD (ADAD).ResultWe observed both common and unique CSF proteomic alterations in DS compared to LOAD and ADAD. Common changes included increased levels of 14‐3‐3 proteins, glucose metabolism, immune activation, and decreased levels in neurosecretory and neuropentraxin synaptic markers. Common changes were strongly correlated to tau and Aβ pathology, and like ADAD, most CSF protein changes occurred prior to the onset of cognitive symptoms. Compared to LOAD, DS showed markedly early elevations in complement, immunoglobulins, extracellular matrix and plasma proteins, suggesting early dysfunction in immune‐related processes and blood‐brain barrier function. These DS‐related changes were observed to occur prior to the onset of Aβ or tau pathology. In contrast to the progression observed in ADAD, in DS neurofilament light was increased prior to total tau levels, which were in turn increased prior to pTau levels, suggesting relatively earlier white matter and axonal dysfunction in DS. Neuronal and neurosecretory proteins were also decreased earlier in DS than in ADAD, consistent with early neuronal dysfunction in DS. Compared to LOAD, DS demonstrated more significant elevations in endosome/lysosome markers in symptomatic phases of the disease.ConclusionEarly pathological alterations in immune function and the blood‐brain barrier associated with trisomy 21 may contribute to the onset of AD pathology in DS. While most pathological alterations are shared between DS, ADAD, and LOAD, the temporal ordering of these pathological changes in DS has unique features.
Outdoor air pollution as a risk factor for Alzheimer’s disease: A systematic review
Authors: Dhillon Gurneet , Hassan Nehal , Wilson Sarah , Ardle Ríona Mc , Su Li , Slight Sarah 
Published: January 2025

AbstractBackgroundOutdoor air pollution is a global issue which poses a significant health risk. Modern neuroimaging techniques have revealed the detrimental impact of air pollution on brain health, in particular the development and progression of neurodegenerative diseases such as Alzheimer’s disease (AD).(1) We conducted a systematic review to evaluate the effects of long‐term (months to years) exposure to outdoor air pollutants on the development and progression of AD using neuroimaging data.MethodThis review followed PRISMA guidelines and registered in PROSPERO (CRD42023482979). Four large databases (MEDLINE, Embase, Scopus, and CINAHL) were systematically searched using words relating to “air pollution”, “neuroimaging”, and “Alzheimer’s disease”. The population researched was kept broad to include all ages. There were no geographical limits applied, and so included all countries. Articles were exported to Endnote (Endnote X9.3.3, Clarivate US), where duplicate articles were removed. Remaining articles were uploaded to the Rayyan and screened for eligibility. The Newcastle Ottawa Scale was used to assess the quality of included papers. A narrative synthesis was conducted, which involved grouping papers that focused on the same neuroimaging outcome and comparing and contrasting between studies.ResultOur search yielded 397 results, after removing duplicated (n=172), articles were removed at the title (n=192), abstract (n=8), and full text (n=17) stages. Eight articles met our inclusion criteria and focused on changes to white matter (n= 5), cortical thickness (n= 6), and grey matter (n= 2). Specific air pollutants (e.g., PM2.5) were associated with white matter reductions, and PM10 and NO2 with reduced cortical thickness. However, higher exposure to NOx and NO2 was linked to better performance in cognition tests. Exposure to PM2.5 was associated with reduced grey matter, with study participants showing greater cognitive impairment. Air pollution exposure was associated with brain structure changes which are commonly seen in AD‐related pathology.ConclusionOur results highlighted significant associations between specific air pollutant exposure and changes in different brain structures. Future research is needed to further investigate the relationship between air pollution exposure and cognitive decline.References:Block ML, Calderón‐Garcidueñas L. Air pollution: mechanisms of neuroinflammation and CNS disease. Trends Neurosci. 2009;32(9):506‐16.