Progressive Cognitive Decline Research Articles

Navβ2 Intracellular Fragments Contribute to Aβ1-42-Induced Cognitive Impairment and Synaptic Deficit Through Transcriptional Suppression of BDNF.

A pathological hallmark of Alzheimer's disease (AD) is the region-specific accumulation of the amyloid-beta protein (Aβ), which triggers aberrant neuronal excitability, synaptic impairment, and progressive cognitive decline. Previous works have demonstrated that Aβ pathology induced aberrant elevation in the levels and excessive enzymatic hydrolysis of voltage-gated sodium channel type 2 beta subunit (Navβ2) in the brain of AD models, accompanied by alteration in excitability of hippocampal neurons, synaptic deficits, and subsequently, cognitive dysfunction. However, the mechanism is unclear. In this research, by employing cell models treated with toxic Aβ1-42 and AD mice, the possible effects and potential mechanisms induced by Navβ2. The results reveal that Aβ1-42 induces remarkable increases in Navβ2 intracellular domain (Navβ2-ICD) and decreases in both BDNF exons and protein levels, as well as phosphorylated tropomyosin-related kinase B (pTrkB) expression in cells and mice, coupled with cognitive impairments, synaptic deficits, and aberrant neuronal excitability. Administration with exogenous Navβ2-ICD further enhances these effects induced by Aβ1-42, while interfering the generation of Navβ2-ICD and/or complementing BDNF neutralize the Navβ2-ICD-conducted effects. Luciferase reporter assay verifies that Navβ2-ICD regulates BDNF transcription and expression by targeting its promoter. Collectively, our findings partially elucidate that abnormal enzymatic hydrolysis of Navβ2 induced by Aβ1-42-associated AD pathology leads to intracellular Navβ2-ICD overload, which may responsible to abnormal neuronal excitability, synaptic deficit, and cognition dysfunction, through its transcriptional suppression on BDNF. Therefore, this work supplies novel evidences that Navβ2 plays crucial roles in the occurrence and progression of cognitive impairment of AD by transcriptional regulatory activity of its cleaved ICD.

Rapid Alzheimer's Disease Diagnosis Using Advanced Artificial Intelligence Algorithms

Alzheimer's disease (AD) is a leading cause of dementia, predominantly impacting the elderly and characterized by progressive cognitive decline. Early and precise detection is critical for effective management and improved patient outcomes. Traditional diagnostic methods such as neuroimaging and cerebrospinal fluid analysis are often invasive, expensive, and time- consuming. Advances in artificial intelligence (AI) and machine learning (ML) provide promising alternatives that are non-invasive, efficient, and cost-effective. This study explores the application of various ML algorithms to predict Alzheimer's disease. The methodology involved data preprocessing and feature selection using the Spearman algorithm to enhance computational efficiency and model performance. We evaluated k-Nearest Neighbors (k-NN), Naive Bayes (NB), Decision Trees (DT), and Ensemble methods. Results indicate that the Ensemble method achieved a predictive accuracy of 94.07% using only 13 features. These results demonstrate the potential of ML algorithms in revolutionizing AD diagnostics, offering scalable and accurate solutions for early detection.

Brain structure, amyloid, and behavioral features for predicting clinical progression in subjective cognitive decline.

As a potential preclinical stage of Alzheimer's dementia, subjective cognitive decline (SCD) reveals a higher risk of future cognitive decline and conversion to dementia. However, it has not been clear whether SCD status increases the clinical progression of older adults in the context of amyloid deposition, cerebrovascular disease (CeVD), and psychiatric symptoms. We identified 99 normal controls (NC), 15 SCD individuals who developed mild cognitive impairment in the next 2 years (P-SCD), and 54 SCD individuals who did not (S-SCD) from ADNI database with both baseline and 2-year follow-up data. Total white matter hyperintensity (WMH), WMH in deep (DWMH) and periventricular (PWMH) regions, and voxel-wise grey matter volumes were compared among groups. Furthermore, using structural equation modelling method, we constructed path models to explore SCD-related brain changes longitudinally and to determine whether baseline SCD status, age, and depressive symptoms affect participants' clinical outcomes. Both SCD groups showed higher baseline amyloid PET SUVR, baseline PWMH volumes, and larger increase of PWMH volumes over time than NC. In contrast, only P-SCD had higher baseline DWMH volumes and larger increase of DWMH volumes over time than NC. No longitudinal differences in grey matter volume and amyloid was observed among NC, S-SCD, and P-SCD. Our path models demonstrated that SCD status contributed to future WMH progression. Further, baseline SCD status increases the risk of future cognitive decline, mediated by PWMH; baseline depressive symptoms directly contribute to clinical outcomes. In conclusion, both S-SCD and P-SCD exhibited more severe CeVD than NC. The CeVD burden increase was more pronounced in P-SCD. In contrast with the direct association of depressive symptoms with dementia severity progression, the effects of SCD status on future cognitive decline may manifest via CeVD pathologies. Our work highlights the importance of multi-modal longitudinal designs in understanding the SCD trajectory heterogeneity, paving the way for stratification and early intervention in the preclinical stage. PRACTITIONER POINTS: Both S-SCD and P-SCD exhibited more severe CeVD at baseline and a larger increase of CeVD burden compared to NC, while the burden was more pronounced in P-SCD. Baseline SCD status increases the risk of future PWMH and DWMH volume accumulation, mediated by baseline PWMH and DWMH volumes, respectively. Baseline SCD status increases the risk of future cognitive decline, mediated by baseline PWMH, while baseline depression status directly contributes to clinical outcome.

The hereditary vessel disease CADASIL

Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a hereditary small vessel disease of the brain characterized by progressive white matter lesions, subcortical infarcts, and cognitive decline. This autosomal dominant disorder is caused by mutations in the NOTCH3 gene located on chromosome 19, resulting in the accumulation of granular osmiophilic material within the walls of small arteries and arterioles. Clinically, CADASIL typically manifests in mid-adulthood with recurrent ischemic events, migraine with aura, mood disturbances, and cognitive impairment. Neuroimaging plays a crucial role in the diagnosis of CADASIL, with characteristic findings including white matter hyperintensities particularly in the anterior temporal lobe and external capsule.

The effects of omega-3, DHA, EPA, Souvenaid® in Alzheimer's disease: A systematic review and meta-analysis.

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Omega-3 fatty acids (n-3-PUFA) are essential to normal neural development and function. Souvenaid®, a medical supplement that contains n-3-PUFA's: eicosatetraenoic acid (EPA) and docosahexaenoic acid (DHA), has emerged as an alternative, slowing cognitive decline in AD patients. In this study, we investigated the effect of dietary supplementation with n-3-PUFA, EPA, DHA, and Souvenaid® in AD patients. This systematic review and meta-analysis aim to establish the relationship between n-3-PUFA, EPA, DHA, and Souvenaid® with cognitive effects, ventricular volume and adverse events in AD patients. A systematic search of randomized control trials (RCT), cohorts, and case-control studies was done in PubMed, Scopus, Web of Science, Cochrane, and Embase for AD adult patients with dietary supplementation with n-3-PUFA, EPA, DHA, or Souvenaid® between 2003 and 2024. We identified 14 studies with 2766 subjects aligned with our criteria. Most publications described positive cognitive outcomes from supplements (58%). The most common adverse events reported were gastrointestinal symptoms. CDR scale showed reduced progression of cognitive decline (SMD = -0.4127, 95% CI: [-0.5926; -0.2327]), without subgroup differences between different dietary supplement interventions. ADCS-ADL, MMSE, ADAS-cog, adverse events, and ventricular volume did not demonstrate significant differences. However, Souvenaid® showed a significant negative effect (SMD = -0.3593, 95% CI: -0.5834 to -0.1352) in ventricular volumes. The CDR scale showed reduced progression of cognitive decline among patients with n-3-PUFA supplemental interventions, with no differences between different n-3-PUFA supplements.

High frequency post-pause word choices and task-dependent speech behavior characterize connected speech in individuals with mild cognitive impairment.

Alzheimer's disease (AD) is characterized by progressive cognitive decline, including impairments in speech production and fluency. Mild cognitive impairment (MCI), a prodrome of AD, has also been linked with changes in speech behavior but to a more subtle degree. This study aimed to investigate whether speech behavior immediately following both filled and unfilled pauses (post-pause speech behavior) differs between individuals with MCI and healthy controls (HCs), and how these differences are influenced by the cognitive demands of various speech tasks. Transcribed speech samples were analyzed from both groups across different tasks, including immediate and delayed narrative recall, picture descriptions, and free responses. Key metrics including lexical and syntactic complexity, lexical frequency and diversity, and part of speech usage, both overall and post-pause, were examined. Significant differences in pause usage were observed between groups, with a higher incidence and longer latencies following these pauses in the MCI group. Lexical frequency following filled pauses was higher among MCI participants in the free response task but not in other tasks, potentially due to the relative cognitive load of the tasks. The immediate recall task was most useful at differentiating between groups. Predictive analyses utilizing random forest classifiers demonstrated high specificity in using speech behavior metrics to differentiate between MCI and HCs. Speech behavior following pauses differs between MCI participants and healthy controls, with these differences being influenced by the cognitive demands of the speech tasks. These post-pause speech metrics can be easily integrated into existing speech analysis paradigms.

Virus-like particle (VLP)-based vaccine targeting tau phosphorylated at Ser396/Ser404 (PHF1) site outperforms phosphorylated S199/S202 (AT8) site in reducing tau pathology and restoring cognitive deficits in the rTg4510 mouse model of tauopathy.

Tauopathies, including Alzheimer's disease (AD) and Frontotemporal Dementia (FTD), are histopathologically defined by the aggregation of hyperphosphorylated pathological tau (pTau) as neurofibrillary tangles in the brain. Site-specific phosphorylation of tau occurs early in the disease process and correlates with progressive cognitive decline, thus serving as targetable pathological epitopes for immunotherapeutic development. Previously, we developed a vaccine (Qβ-pT181) displaying phosphorylated Thr181 tau peptides on the surface of a Qβ bacteriophage virus-like particle (VLP) that induced robust antibody responses, cleared pathological tau, and rescued memory deficits in a transgenic mouse model of tauopathy. Here we report the characterization and comparison of two additional Qβ VLP-based vaccines targeting the dual phosphorylation sites Ser199/Ser202 (Qβ-AT8) and Ser396/Ser404 (Qβ-PHF1). Both Qβ-AT8 and Qβ-PHF1 vaccines elicited high-titer antibody responses against their pTau epitopes. However, only Qβ-PHF1 rescued cognitive deficits, reduced soluble and insoluble pathological tau, and reactive microgliosis in a 4-month rTg4510 model of FTD. Both sera from Qβ-AT8 and Qβ-PHF1 vaccinated mice were specifically reactive to tau pathology in human AD post-mortem brain sections. These studies further support the use of VLP-based immunotherapies to target pTau in AD and related tauopathies and provide potential insight into the clinical efficacy of various pTau epitopes in the development of immunotherapeutics.

An effectual recommendation model using hybrid learning models for early detection of Alzheimer’s disease

Alzheimer’s disease (AD) is a neurodegenerative disorder that affects millions of individuals worldwide, causing progressive cognitive decline. Early prediction and diagnosis the AD accurately is crucial for effective intervention and treatment. In this study, we propose a comprehensive framework for AD prediction using various techniques, including preprocessing and denoising with Multilayer Perceptron (MLP) and Ant Colony Optimization (ACO), segmentation using U-Net, and classification with Spatial Pyramid Pooling Network (SPPNet). Furthermore, we employ Convolutional Neural Network (CNN) with SPPNet for training and develop a chatbot for recommendation based on MRI data input. The preprocessing and denoising techniques play a vital role in enhancing the quality of the input data. MLP is utilized for preprocessing, where it effectively handles feature extraction and noise reduction. ACO is employed for denoising, optimizing the data to improve the signal-to-noise ratio, and enhancing the overall performance of subsequent stages. For accurate segmentation of brain regions, we employ the U-Net architecture, which has shown remarkable success in medical image segmentation tasks. U-Net effectively identifies the regions of interest, aiding in subsequent classification stages. The classification phase utilizes SPPNet, a deep learning model known for its ability to capture spatial information at multiple scales. SPPNet extracts features from segmented brain regions, enabling robust classification of AD and non-AD cases. To enhance the training process, we employ CNN with SPPNet, leveraging the power of convolutional layers to capture intricate patterns and improve predictive accuracy. The CNN-SPPNet model is trained on a large dataset of MRI scans, enabling it to learn complex representations and make accurate predictions. Hence the proposed work can be integrated with a chatbot that takes MRI data as input and provides recommendations based on the predicted AD probability. Experimental evaluation shows that the combination of preprocessing, denoising, segmentation, and classification offers a comprehensive solution for accurate and efficient AD diagnosis and management.

Predictive Models for the Transition from Mild Neurocognitive Disorder to Major Neurocognitive Disorder: Insights from Clinical, Demographic, and Neuropsychological Data.

Neurocognitive disorders (NCDs) are progressive conditions that severely impact cognitive function and daily living. Understanding the transition from mild to major NCD is crucial for personalized early intervention and effective management. Predictive models incorporating demographic variables, clinical data, and scores on neuropsychological and emotional tests can significantly enhance early detection and intervention strategies in primary healthcare settings. We aimed to develop and validate predictive models for the progression from mild NCD to major NCD using demographic, clinical, and neuropsychological data from 132 participants over a two-year period. Generalized Estimating Equations were employed for data analysis. Our final model achieved an accuracy of 83.7%. A higher body mass index and alcohol drinking increased the risk of progression from mild NCD to major NCD, while female sex, higher praxis abilities, and a higher score on the Geriatric Depression Scale reduced the risk. Here, we show that integrating multiple factors-ones that can be easily examined in clinical settings-into predictive models can improve early diagnosis of major NCD. This approach could facilitate timely interventions, potentially mitigating the progression of cognitive decline and improving patient outcomes in primary healthcare settings. Further research should focus on validating these models across diverse populations and exploring their implementation in various clinical contexts.

Regulation of mitochondrial dysfunction by estrogens and estrogen receptors in Alzheimer's disease: A focused review.

Alzheimer's disease (AD) is a neurodegenerative disorder that primarily manifests itself by progressive memory loss and cognitive decline, thus significantly affecting memory functions and quality of life. In this review, we proceed from the understanding that the canonical amyloid-β hypothesis, while significant, has faced setbacks, highlighting the need to adopt a broader perspective considering the intricate interplay of diverse pathological pathways for effective AD treatments. Sex differences in AD offer valuable insights into a better understanding of its pathophysiology. Fluctuation of the levels of ovarian sex hormones during perimenopause is associated with changes in glucose metabolism, as a possible window of opportunity to further understand the roles of sex steroid hormones and their associated receptors in the pathophysiology of AD. We review these dimensions, emphasizing the potential of estrogen receptors (ERs) to reveal mitochondrial functions in the search for further research and therapeutic strategies for AD pharmacotherapy. Understanding and addressing the intricate interactions of mitochondrial dysfunction and ERs potentially pave the way for more effective approaches to AD therapy.

Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points.

Alzheimer's disease (AD) is the most common form of dementia and is characterized by progressive memory loss and cognitive decline, affecting behavior, speech, and motor abilities. The neuropathology of AD includes the formation of extracellular amyloid-β plaque and intracellular neurofibrillary tangles of phosphorylated tau, along with neuronal loss. While neuronal loss is an AD hallmark, cell-cell communication between neuronal and non-neuronal cell populations maintains neuronal health and brain homeostasis. To study changes in cell-cell communication during disease progression, we performed snRNA-sequencing of the hippocampus from female 3xTg-AD and wild-type littermates at 6 and 12 months. We inferred differential cell-cell communication between 3xTg-AD and wild-type mice across time points and between senders (astrocytes, microglia, oligodendrocytes, and OPCs) and receivers (excitatory and inhibitory neurons) of interest. We also assessed the downstream effects of altered glia-neuron communication using pseudobulk differential gene expression, functional enrichment, and gene regulatory analyses. We found that glia-neuron communication is increasingly dysregulated in 12-month 3xTg-AD mice. We also identified 23 AD-associated ligand-receptor pairs that are upregulated in the 12-month-old 3xTg-AD hippocampus. Our results suggest increased AD association of interactions originating from microglia. Signaling mediators were not significantly differentially expressed but showed altered gene regulation and TF activity. Our findings indicate that altered glia-neuron communication is increasingly dysregulated and affects the gene regulatory mechanisms in neurons of 12-month-old 3xTg-AD mice.

Spatial Multi-Omics in Alzheimer’s Disease: A Multi-Dimensional Approach to Understanding Pathology and Progression

Alzheimer’s Disease (AD) presents a complex neuropathological landscape characterized by hallmark amyloid plaques and neurofibrillary tangles, leading to progressive cognitive decline. Despite extensive research, the molecular intricacies contributing to AD pathogenesis are inadequately understood. While single-cell omics technology holds great promise for application in AD, particularly in deciphering the understanding of different cell types and analyzing rare cell types and transcriptomic expression changes, it is unable to provide spatial distribution information, which is crucial for understanding the pathological processes of AD. In contrast, spatial multi-omics research emerges as a promising and comprehensive approach to analyzing tissue cells, potentially better suited for addressing these issues in AD. This article focuses on the latest advancements in spatial multi-omics technology and compares various techniques. Additionally, we provide an overview of current spatial omics-based research results in AD. These technologies play a crucial role in facilitating new discoveries and advancing translational AD research in the future. Despite challenges such as balancing resolution, increasing throughput, and data analysis, the application of spatial multi-omics holds immense potential in revolutionizing our understanding of human disease processes and identifying new biomarkers and therapeutic targets, thereby potentially contributing to the advancement of AD research.

Effects and mechanisms of computerized cognitive training in Huntington's disease: protocol for a pilot study

Huntington's disease (HD) causes progressive cognitive decline, with no available treatments. Computerized cognitive training (CCT) has shown efficacy in other populations, but its effects in HD are largely unknown. This pilot study will explore the effects and neural mechanisms of CCT in HD. The intervention group participants will complete 12 weeks of multidomain CCT. Control group participants will receive lifestyle education and access to CCT after the study. The primary outcome is change in processing speed. Secondary outcomes include – change in other cognitive domains, functional brain network connectivity (derived from MRI) and psychosocial function. Feasibility outcomes include rates of recruitment, adherence and retention. This study may provide insights into the effects of CCT in HD and guide future trials. Clinical Trial Registration: ACTRN12622000908730 ( ClinicalTrials.gov )

The Association of Circulating Glucagon-Like Peptide-1 with Cognitive Functions and Biomarkers in Alzheimer's Disease.

Alzheimer's disease (AD) is an age-related neurodegenerative disease that is clinically characterized by progressive cognitive decline. Glucagon-like peptide-1 (GLP-1) is a hormone that belongs to the incretin family and is released in response to nutrient intake. It plays a role in maintaining metabolic homeostasis and has been suggested to be involved in maintaining the brain microenvironment. However, the role of GLP-1 in AD pathogenesis has not been fully illustrated. This study aims to investigate the clinical relevance of GLP-1 in AD and the effects of GLP-1 in amyloid-β (Aβ) metabolism in vitro. In this study, 39 AD patients and 120 cognitively intact controls were included. Plasma levels of GLP-1 were measured using ELISA. SH-SY5Y cells overexpressing human amyloid precursor protein (APP) were treated with GLP-1. Western blot analysis was used to assess the effects of GLP-1 on the metabolism of Aβ. Plasma GLP-1 levels were decreased with aging. Plasma GLP-1 levels were lower in AD patients in comparison with healthy older adults. Plasma GLP-1 levels were positively associated with Mini-Mental State Examination scores but negatively associated with plasma pTau181 levels. GLP-1 dose-dependently increased the area fraction of mitochondrial staining in vitro. Furthermore, GLP-1 dose-dependently promoted the α-cleavage of APP, thus reducing the generation of Aβ. GLP-1 has neuroprotective effects in AD, and therefore the decrease in GLP-1 levels during aging might contribute to the development of AD.

Cerebrospinal fluid α-synuclein adds the risk of cognitive decline and is associated with tau pathology among non-demented older adults

BackgroundThe role of α-synuclein in dementia has been recognized, yet its exact influence on cognitive decline in non-demented older adults is still not fully understood.MethodsA total of 331 non-demented individuals were included in the study from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Participants were divided into two distinct groups based on their α-synuclein levels: one with lower levels (α-synuclein-L) and another with higher levels (α-synuclein-H). Measurements included neuropsychiatric scales, cerebrospinal fluid (CSF) biomarkers, and blood transcriptomics. The linear mixed-effects model investigated the longitudinal changes in cognition. Kaplan-Meier survival analysis and the Cox proportional hazards model were utilized to evaluate the effects of different levels of α-synuclein on dementia. Gene set enrichment analysis (GSEA) was utilized to investigate the biological pathways related to cognitive impairment. Pearson correlation, multiple linear regression models, and mediation analysis were employed to investigate the relationship between α-synuclein and neurodegenerative biomarkers, and their potential mechanisms affecting cognition.ResultsHigher CSF α-synuclein levels were associated with increased risk of cognitive decline and progression to dementia. Enrichment analysis highlighted the activation of tau-associated and immune response pathways in the α-synuclein-H group. Further correlation and regression analysis indicated that the CSF α-synuclein levels were positively correlated with CSF total tau (t-tau), phosphorylated tau (p-tau) 181, tumor necrosis factor receptor 1 (TNFR1) and intercellular cell adhesion molecule-1 (ICAM-1). Mediation analysis further elucidated that the detrimental effects of CSF α-synuclein on cognition were primarily mediated through CSF t-tau and p-tau. Additionally, it was observed that CSF α-synuclein influenced CSF t-tau and p-tau181 levels via inflammatory pathways involving CSF TNFR1 and ICAM-1.ConclusionsThese findings elucidate a significant connection between elevated levels of CSF α-synuclein and the progression of cognitive decline, highlighting the critical roles of activated inflammatory pathways and tau pathology in this association. They underscore the importance of monitoring CSF α-synuclein levels as a promising biomarker for identifying individuals at increased risk of cognitive deterioration and developing dementia.

Neuroprogression in bipolar disorder: why right is wrong.

The controversy on whether bipolar disorder is a neurodevelopmental versus a neuroprogressive illness is still around, despite some reductionistic claims that only one model is right. The current diagnostic classifications are not helpful to address this issue, and there is conflicting evidence in favor and against either model. In practice, though, understanding that many patients may show a progressive cognitive and functional decline which may be correlated with the number and severity of episodes may lead to better outcomes through early intervention strategies.

Postoperative Delirium and the Older Adult: Untangling the Confusion.

Postoperative delirium is one of the most prevalent postoperative complications, affecting mostly older adults. Its incidence is expected to rise because of surgical advances, shifting demographics, and increased life expectancy. Although an acute alteration in brain function, postoperative delirium is associated with adverse outcomes, including progressive cognitive decline and dementia, that place significant burdens on patients' lives and healthcare systems. This has prompted efforts to understand the mechanisms of postoperative delirium to provide effective prevention and treatment. There are multiple mechanisms involved in the etiology of postoperative delirium that share similarities with the physiological changes associated with the aging brain. In addition, older patients often have multiple comorbidities including increased cognitive impairment that is also implicated in the genesis of delirium. These tangled connections pinpointed a shift toward creation of a holistic model of the pathophysiology of postoperative delirium. Scientific advancements integrating clinical risk factors, possible postoperative delirium biomarkers, genetic features, digital platforms, and other biotechnical and information technological innovations, will become available in the near future. Advances in artificial intelligence, for example, will aggregate cognitive testing platforms with patient-specific postoperative delirium risk stratification studies, panels of serum and cerebrospinal fluid molecules, electroencephalogram signatures, and gut microbiome features, along with the integration of novel polygenetic variants of sleep and cognition. These advances will allow for the enrollment of high-risk patients into prevention programs and help uncover new pharmacologic targets.

Non-linear relationship of serum albumin-to-globulin ratio and cognitive function in American older people: a cross-sectional national health and nutrition examination survey 2011-2014 (NHANES) study.

Inflammation and liver function are associated with cognitive decline and dementia. Little is known about the serum albumin-to-globulin ratio on cognitive function. The objective of this study was to investigate the association between albumin-to-globulin ratio and cognitive function among the American older people. The public data available on the US National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014 was used for this cross-sectional study. Participants aged ≥60 years completed the cognitive function assessments, including word learning and recall modules from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), the animal fluency (AF) test, and the digit symbol substitution test (DSST). A composite cognition score was calculated to evaluate global cognition. The univariate and multivariate linear regression analysis, curve fitting, a threshold effect, along with a subgroup analysis and interaction tests were conducted. Serum albumin-to-globulin ratio (per 0.1 unit) was positively associated DSST score (β = 0.36, 95% CI: 0.21, 0.51), AF score (β = 0.1, 95% CI: 0.04, 0.16) and global cognition score (β = 0.05, 95% CI: 0.02, 0.07), after being fully adjusted, while albumin-to-globulin ratio was not related to CERAD score (β = 0.05, 95% CI: -0.02, 0.12). A non-linear was observed in the dose-response relationship between albumin-to-globulin ratio and global cognition (P for non-linearity < 0.001). The subgroup analysis was overall stable, yet the interaction test was significant for age on global cognition (P for interaction = 0.036). The findings of this cross-sectional study suggested a positive and non-linear association between albumin-to-globulin ratio and cognitive function in the American older people. Maintaining albumin-to-globulin ratio with an appropriate range may be one of the therapeutic strategies to limit the progression of cognitive decline for the older people.

P025 Routine Giant-cell arteritis turned Heidenhain variant of sporadic Creutzfeldt-Jakob disease: a mysterious case report!

Abstract Background/Aims Giant-cell arteritis (GCA) is a large vessel vasculitis predominantly affecting those above 50 years of age. Creutzfeldt-Jacob disease (CJD) is not a well-recognised differential diagnosis of GCA presentation. Prion diseases are progressive, currently untreatable and ultimately fatal. Methods We report the case of a 76-year-old female who had an eventful hospital stay of 37 days. She has a history of asthma, hypertension, ulcerative colitis and right-sided GCA 5 years back (normal inflammatory markers &amp; biopsy). Results The patient presents to Harlow ED with a right temporal headache with tenderness, jaw claudication symptoms, blurred vision, diplopia, dizziness and painful right eye movements. Her CRP was &amp;lt;1 and ESR was 5. The plan was to treat it as a recurrence of her GCA and to continue with the high dose Prednisolone started by the ED. CT Head was normal. Owing to poor response, IV Methyl Pred was given. On day six, patient was re-admitted with worsening headache and generalised decline. Ophthalmology review noted multiple visual field defects and treated as GCA. A neurology review noted the patient to be encephalopathic. Advice was for MRI head and CSF analysis - both NAD. On day 12 she had ongoing headache, diplopia, poor vision/memory, and reduced hearing in right ear, but alert and following instructions. On day 17, ENT suggestion was to treat as Meniere’s and start on Betahistine. On day 22, the patient had a TIA episode and discussed with Stroke team. Repeat CT Head was nil acute. By day 26, the patient was unresponsive intermittently and was treated as hypoactive delirium. On day 31 a seizure activity was noticed. Neurology review on day 33 noted rapid decline- the patient being mute, seizure/atypical encephalitis. MRI-Head with contrast showed the possibility of CJD. The very next day patient was reviewed by the team from National CJD Research and Surveillance team, Edinburgh. The formal diagnosis given was: probable Sporadic CJD (visual/Heidanhain variant), rapidly progressive cognitive decline with visual signs, myoclonus, and akinetic mutism, positive MRIs, bland CSF, no clear iatrogenic or variant risk factors, and no credible alternative diagnosis. The distressed family members were updated and the patient was put on EoL pathway. She died peacefully four days later (Day 37). Conclusion The importance of this case is the conflicting inputs from at least five specialities in a rapidly deteriorating patient. A background of previous right-sided GCA did prompt initial treatment in those lines. MRI Head DWI sequence did show the classic ‘cortical ribboning’ with right caudate and lentiform hyperintensity; which clinched the mysterious diagnosis of this rare disease which requires public health surveillance. CJD is to be suspected in any undiagnosed rapidly progressive mental deterioration or dementia, often with behavioural abnormalities and myoclonus. Disclosure S. Narikkoottungal: None. K. Gunasekera: None. K. Ahmed: None.

Thy1-ApoE4/C/EBPβ double transgenic mice act as a sporadic model with Alzheimer's disease.

Early onset familial Alzheimer's disease (FAD) with APP, PS1/2 (presenilins) mutation accounts for only a small portion of AD cases, and most are late-onset sporadic. However, majority of AD mouse models are developed to mimic the genetic cause of human AD by overexpressing mutated forms of human APP, PS1/2, and/or Tau protein, though there is no Tau mutation in AD, and no single mouse model recapitulates all aspects of AD pathology. Here, we report Thy1-ApoE4/C/EBPβ double transgenic mouse model that demonstrates key AD pathologies in an age-dependent manner in absence of any human APP or PS1/2 mutation. Using the clinical diagnosis criteria, we show that this mouse model exhibits tempo-spatial features in AD patient brains, including progressive cognitive decline associated with brain atrophy, which is accompanied with extensive neuronal degeneration. Remarkably, the mice display gradual Aβ aggregation and neurofibrillary tangles formation in the brain validated by Aβ PET and Tau PET. Moreover, the mice reveal widespread neuroinflammation as shown in AD brains. Hence, Thy1-ApoE4/C/EBPβ mouse model acts as a sporadic AD mouse model, reconstituting the major AD pathologies.