Alzheimer's Disease Research Research Articles

Pathological and neurochemical correlates of locus coeruleus functional network activity

The locus coeruleus (LC) produces the neuromodulators norepinephrine and dopamine, and projects widely to subcortical and cortical brain regions. The LC has been a focus of neuroimaging biomarker development for the early detection of Alzheimer’s disease (AD) since it was identified as one of the earliest brain regions to develop tau pathology. Our recent research established the use of positron emission tomography (PET) to measure LC catecholamine synthesis capacity in cognitively unimpaired older adults. We extend this work by investigating the possible influence of pathology and LC neurochemical function on LC network activity using functional magnetic resonance imaging (fMRI). In separate sessions, participants underwent PET imaging to measure LC catecholamine synthesis capacity ([18F]Fluoro-m-tyrosine), tau pathology ([18F]Flortaucipir), and amyloid-β pathology ([11C]Pittsburgh compound B), and fMRI imaging to measure LC functional network activity at rest. Consistent with a growing body of research in aging and preclinical AD, we find that higher functional network activity is associated with higher tau burden in individuals at risk of developing AD (amyloid-β positive). Critically, relationships between higher LC network activity and higher pathology (amyloid-β and tau) were moderated by LC catecholamine synthesis capacity. High levels of LC catecholamine synthesis capacity reduced relationships between higher network activity and pathology. Broadly, these findings support the view that individual differences in functional network activity are shaped by interactions between pathology and neuromodulator function, and point to catecholamine systems as potential therapeutic targets.

Computational 3D Models of Fe2+/3+-Aβ1-42 Complexes Associated with Alzheimer's Disease.

The interaction between iron and amyloid-beta (Aβ) peptides has received significant attention in Alzheimer's disease (AD) research due to its potential implications in developing this pathology. However, the coordination preferences of iron and Aβ1-42 have not been thoroughly investigated or remain unknown. This study employs a computational protocol that combines homology modeling techniques with quantum mechanics (DTF-xTB) calculations to build and evaluate several 3D models of Fe2+/3+-Aβ1-42. Our results reveal well-defined complexes for both the metal and peptide moieties, and we discuss the molecular interactions stabilizing these complexes by elucidating the coordinating environments and binding preferences. These proposed models offer valuable insights into the role of iron in Alzheimer's disease (AD) pathology.

Cognitive Assessment with Cognivue Clarity®: Psychometric Properties and Normative Ranges in a Diverse Population.

Detecting cognitive impairment in clinical practice is challenging as most instruments do not perform well in diverse samples of older adults. These same instruments are often used for eligibility into clinical trials making it difficult to recruit minoritized adults into Alzheimer's disease (AD) studies. Cognivue Clarity® is an FDA-cleared computerized 10-minute cognitive screening platform using adaptive psychophysics to detect cognitive impairment. Test the ability of Cognivue Clarity to measure cognitive performance in a diverse community sample compared with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). This study enrolled 452 participants across 6 US study sites and completed both Cognivue Clarity device and RBANS. Psychometric properties and exploratory factor analysis of Cognivue Clarity were explored and comparisons against RBANS across different age, sex, education, and ethnoracial groups were conducted. Participants had a mean age of 47.9±16.1 years (range: 18-85), 63.6% were female, 45.9% had ≤12 years of education, 31.2% were African American and 9.2% were Hispanic. Cognivue Clarity had strong internal consistency, test-retest reliability and minimal practice effects. A 4-factor structure (Memory, Attention, Visuomotor, and Discrimination) had excellent goodness-of-fit. Normalizing age effects improved performance. Race and education effects were similar to those seen with RBANS. Cognivue Clarity had strong correlations with RBANS. Our study supports the use of Cognivue Clarity as an easy-to-use, brief, and valid cognitive assessment that measures cognitive performance. In the correct clinical setting, Cognivue Clarity may identify individuals with likely cognitive impairment who could be candidates for AD research studies.

Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center

The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease.

Geospatial Applications in Alzheimer’s Disease Research and Beyond: A Systematic Review

With the increasing prevalence and social impacts of Alzheimer’s disease (AD), innovative approaches to our understanding of its etiology, progression, and potential interventions are critical. Geospatial applications are a promising tool in addressing the complex spatial and temporal dynamics of AD. A substantial knowledge gap remains, however, regarding the comprehensive utilization and impact of geospatial applications in AD research. We comprehensively consider the current status of geospatial-information application in AD based on 159 research articles on geospatial applications published between 1991 and 2022 from the Web of Science and PubMed databases. Four main research themes are identified: geographic environmental factors, geographic disparities, activity behaviors, and care services. Geospatial information has been extensively applied using techniques such as spatial clustering and hotspot analysis. We investigate the influence of location and spatial factors on AD risk, the activity behavior of patients with AD using location data and spatial analysis, and medical-resource proximity via geospatial modeling and predictive analysis. Additionally, we identify three knowledge gaps: geographic environment measurement, spatiotemporal contrastive analysis of disease prevalence, and multidisciplinary integration. The review underscores the value of geospatial information in AD-related research and public health, offering researchers insights into prospective directions and collaborative opportunities with geographers.

Moderate aerobic training enhances the effectiveness of insulin therapy through hypothalamic IGF1 signaling in rat model of Alzheimer's disease

Alzheimer's disease (AD) is a neurological condition that is connected with a decline in a person's memory as well as their cognitive ability. One of the key topics of AD research has been the exploration of metabolic causes. We investigated the effects of treadmill exercise and intranasal insulin on learning and memory impairment and the expression of IGF1, BDNF, and GLUT4 in hypothalamus. The animals were put into 9 groups at random. In this study, we examined the impact of insulin on spatial memory in male Wistar rats and analyzed the effects of a 4-week pretreatment of moderate treadmill exercise and insulin on the mechanisms of improved hypothalamic glucose metabolism through changes in gene and protein expression of IGF1, BDNF, and GLUT4. We discovered that rat given Aβ25–35 had impaired spatial learning and memory, which was accompanied by higher levels of Aβ plaque burden in the hippocampus and lower levels of IGF1, BDNF, and GLUT4 mRNA and protein expression in the hypothalamus. Additionally, the administration of exercise training and intranasal insulin results in the enhancement of spatial learning and memory impairments, the reduction of plaque burden in the hippocampus, and the enhancement of the expression of IGF1, BDNF, and GLUT4 in the hypothalamus of rats that were treated with Aβ25–35. Our results show that the improvement of learning and spatial memory due to the improvement of metabolism and upregulation of the IGF1, BDNF, and GLUT4 pathways can be affected by pretreatment exercise and intranasal insulin.

Progress in mitochondrial and omics studies in Alzheimer's disease research: from molecular mechanisms to therapeutic interventions.

Alzheimer's disease (Alzheimer's disease, AD) is a progressive neurological disorder characterized by memory loss and cognitive impairment. It is characterized by the formation of tau protein neurofibrillary tangles and β-amyloid plaques. Recent studies have found that mitochondria in neuronal cells of AD patients exhibit various dysfunctions, including reduced numbers, ultrastructural changes, reduced enzyme activity, and abnormal kinetics. These abnormal mitochondria not only lead to the loss of normal neuronal cell function, but are also a major driver of AD progression. In this review, we will focus on the advances of mitochondria and their multi-omics in AD research, with particular emphasis on how mitochondrial dysfunction in AD drives disease progression. At the same time, we will focus on summarizing how mitochondrial genomics technologies have revealed specific details of these dysfunctions and how therapeutic strategies targeting mitochondria may provide new directions for future AD treatments. By delving into the key mechanisms of mitochondria in AD related to energy metabolism, altered kinetics, regulation of cell death, and dysregulation of calcium-ion homeostasis, and how mitochondrial multi-omics technologies can be utilized to provide us with a better understanding of these processes. In the future, mitochondria-centered therapeutic strategies will be a key idea in the treatment of AD.

Navigating the Alzheimer's Treatment Landscape: Unraveling Amyloid-Beta Complexities and Pioneering Precision Medicine Approaches.

A variety of cutting-edge methods and good knowledge of the illness's complex causes are causing a sea change in the field of Alzheimer's Disease (A.D.) research and treatment. Precision medicine is at the vanguard of this change, where individualized treatment plans based on genetic and biomarker profiles give a ray of hope for customized therapeutics. Combination therapies are becoming increasingly popular as a way to address the multifaceted pathology of Alzheimer's by simultaneously attacking Aβ plaques, tau tangles, neuroinflammation, and other factors. The article covers several therapeutic design efforts, including BACE inhibitors, gamma- secretase modulators, monoclonal antibodies (e.g., Aducanumab and Lecanemab), and anti- Aβ vaccinations. While these techniques appear promising, clinical development faces safety concerns and uneven efficacy. To address the complicated Aβ pathology in Alzheimer's disease, a multimodal approach is necessary. The statement emphasizes the continued importance of clinical trials in addressing safety and efficacy concerns. Looking ahead, it suggests that future treatments may take into account genetic and biomarker traits in order to provide more personalized care. Therapies targeting Aβ, tau tangles, neuroinflammation, and novel drug delivery modalities are planned. Nanoparticles and gene therapies are only two examples of novel drug delivery methods that have the potential to deliver treatments more effectively, with fewer side effects, and with better therapeutic results. In addition, medicines that target tau proteins in addition to Aβ are in the works. Early intervention, based on precise biomarkers, is a linchpin of Alzheimer's care, emphasizing the critical need for detecting the disease at its earliest stages. Lifestyle interventions, encompassing diet, exercise, cognitive training, and social engagement, are emerging as key components in the fight against cognitive decline. Data analytics and art are gaining prominence as strategies to mitigate the brain's inflammatory responses. To pool knowledge and resources in the fight against Alzheimer's, international cooperation between scientists, doctors, and pharmaceutical companies is still essential. In essence, a complex, individualized, and collaborative strategy will characterize Alzheimer's research and therapy in the future. Despite obstacles, these encouraging possibilities show the ongoing commitment of the scientific and medical communities to combat A.D. head-on, providing a glimmer of hope to the countless people and families touched by this savage sickness.

Neuroprotective Role of Phytoconstituents-based Nanoemulsion for the Treatment of Alzheimer's Disease.

Alzheimer's disease (AD) is the most prevalent form of neurodegenerative disorder (ND), affecting more than 44 million individuals globally as of 2023. It is characterized by cognitive dysfunction and an inability to perform daily activities. The progression of AD is associated with the accumulation of amyloid beta (Aβ), the formation of neurofibrillary tangles (NFT), increased oxidative stress, neuroinflammation, mitochondrial dysfunction, and endoplasmic reticulum stress. Presently, various phytomedicines and their bioactive compounds have been identified for their neuroprotective effects in reducing oxidative stress, alleviating neuroinflammation, and mitigating the accumulation of Aβ and acetylcholinesterase enzymes in the hippocampus and cerebral cortex regions of the brain. However, despite demonstrating promising anti-Alzheimer's effects, the clinical utilization of phytoconstituents remains limited in scope. The key factor contributing to this limitation is the challenges inherent in traditional drug delivery systems, which impede their effectiveness and efficiency. These difficulties encompass insufficient drug targeting, restricted drug solubility and stability, brief duration of action, and a lack of control over drug release. Consequently, these constraints result in diminished bioavailability and insufficient permeability across the blood-brain barrier (BBB). In response to these challenges, novel drug delivery systems (NDDS) founded on nanoformulations have emerged as a hopeful strategy to augment the bioavailability and BBB permeability of bioactive compounds with poor solubility. Among these systems, nanoemulsion (NE) have been extensively investigated for their potential in targeting AD. NE offers several advantages, such as ease of preparation, high drug loading, and high stability. Due to their nanosize droplets, NE also improves gut and BBB permeability leading to enhanced permeability of the drug in systemic circulation and the brain. Various studies have reported the testing of NE-based phytoconstituents and their bioactives in different animal species, including transgenic, Wistar, and Sprague-Dawley (SD) rats, as well as mice. However, transgenic mice are commonly employed in AD research to analyze the effects of Aβ. In this review, various aspects such as the neuroprotective role of various phytoconstituents, the challenges associated with conventional drug delivery, and the need for NDDS, particularly NE, are discussed. Various studies involving phytoconstituent-based NE for the treatment of AD are also discussed.

Advances of induced pluripotent stem cells in Alzheimer’s disease: A bibliometric analysis

Objective: Alzheimer’s disease (AD), as a progressive neurological disorder that primarily affects memory, thinking skills, and behavior, is the most common cause of dementia, but there is no cure for AD. Induced pluripotent stem cells (iPSCs) therapy, as an emerging therapeutic strategy, brings new hope for the treatment of these diseases. This study aims to explore the research hotspots, development trends and future directions of iPSCs therapy in AD. Methods: By quantitatively analyzing the relevant literature, we screened all Science Citation Index Expanded (SCI-EXPANDED) and Social Sciences Citation Index (SSCI) related literature about iPSCs and AD from 1900-2024 from Web of Science, and analyzed the research trends in this field by using VOSviewer and bibliometric analysis online platforms etc. Results: A total of 718 related literature were screened from the Web of Science Core Collection database according to the search strategy. Bibliometric analysis revealed that the number of publications on iPSCs and AD has shown a growing trend, with an annual average of more than 90 publications over the past five years, which is a hot spot in recent years. Notably, Li-Huei Tsai is the most productive and influential author in the field. Harvard Medical School ranks as the institution with the largest number of publications, while Stem Cell Research stands out as the journal with the most publications on this topic. Furthermore, the United States makes the largest contribution to this field. Conclusions: iPSCs therapy has been become a hot spot in AD research, and the main contributor is from the United States.

Reduced PIN1 expression in neocortical and limbic brain regions in female Alzheimer’s patients correlates with cognitive and neuropathological phenotypes

Women have a higher incidence of Alzheimer’s disease (AD), even after adjusting for increased longevity. Thus, there is an urgent need to identify genes that underpin sex-associated risk of AD. PIN1 is a key regulator of the tau phosphorylation signaling pathway; however, potential differences in PIN1 expression, in males and females, are still unknown. We analyzed brain transcriptomic datasets focusing on sex differences in PIN1 mRNA levels in an aging and AD cohort, which revealed reduced PIN1 levels primarily within females. We validated this observation in an independent dataset (ROS/MAP), which also revealed that PIN1 is negatively correlated with multiregional neurofibrillary tangle density and global cognitive function in females only. Additional analysis revealed a decrease in PIN1 in subjects with mild cognitive impairment (MCI) compared with aged individuals, again driven predominantly by female subjects. Histochemical analysis of PIN1 in AD and control male and female neocortex revealed an overall decrease in axonal PIN1 protein levels in females. These findings emphasize the importance of considering sex differences in AD research.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease.

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis- regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Alzheimer's disease diagnosis by applying Shannon entropy to Ricci flow-based surface indexing and extreme gradient boosting

Geometric surface models are extensively utilized in brain imaging to analyze and compare three-dimensional anatomical shapes. Due to the intricate nature of the brain surface, rather than examining the entire cortical surface, we are introducing a new set of signatures focused on characteristics of the hippocampal region, which is linked to aspects of Alzheimer's disease. Our approach focuses on Ricci flow as a conformal parameterization method, permitting us to calculate the conformal factor and mean curvature as conformal surface representations to identify distinct regions within a three-dimensional mesh. For the first time for such settings, we propose a simple while elegant formulation by employing the well-established concept of Shannon entropy on these well-known features. This compact while rich feature formulation turns out to lead to an efficient local surface encoding. We are validating its effectiveness through a series of preliminary experiments on 3D MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), with the aim of diagnosing Alzheimer's disease. The feature vectors generated and inputted into the XGBoost classifier demonstrate a remarkable level of accuracy, further emphasizing their potential as a valuable additional measure for surface-based cortical morphometry in Alzheimer's disease research.

Downregulation of hsa-miR-132 and hsa-miR-129: non-coding RNA molecular signatures of Alzheimer's disease.

Alzheimer's disease (AD) affects the elderly population by causing memory impairments, cognitive and behavioral abnormalities. Currently, no curative treatments exist, emphasizing the need to explore therapeutic options that modify the progression of the disease. MicroRNAs (miRNAs), as non-coding RNAs, demonstrate multifaceted targeting potential and are known to be dysregulated in AD pathology. This mini review focuses on two promising miRNAs, hsa-miR-132 and hsa-miR-129, which consistently exhibit differential regulation in AD. By employing computational predictions and referencing published RNA sequencing dataset, we elucidate the intricate miRNA-mRNA target relationships associated with hsa-miR-132 and hsa-miR-129. Our review consistently identifies the downregulation of hsa-miR-132 and hsa-miR-129 in AD brains as a non-coding RNA molecular signature across studies conducted over the past 15 years in AD research.

Predicting Driving Cessation Among Cognitively Normal Older Drivers: The Role of Alzheimer Disease Biomarkers and Clinical Assessments.

With the aging US population and increasing incidence of Alzheimer disease (AD), understanding factors contributing to driving cessation among older adults is crucial for clinicians. Driving is integral for maintaining independence and functional mobility, but the risk factors for driving cessation, particularly in the context of normal aging and preclinical AD, are not well understood. We studied a well-characterized community cohort to examine factors associated with driving cessation. This prospective, longitudinal observation study enrolled participants from the Knight Alzheimer Disease Research Center and The DRIVES Project. Participants were enrolled if they were aged 65 years or older, drove weekly, and were cognitively normal (Clinical Dementia Rating [CDR] = 0) at baseline. Participants underwent annual clinical, neurologic, and neuropsychological assessments, including β-amyloid PET imaging and CSF (Aβ42, total tau [t-Tau], and phosphorylated tau [p-Tau]) collection every 2-3 years. The primary outcome was time from baseline visit to driving cessation, accounting for death as a competing risk. The cumulative incidence function of driving cessation was estimated for each biomarker. The Fine and Gray subdistribution hazard model was used to examine the association between time to driving cessation and biomarkers adjusting for clinical and demographic covariates. Among the 283 participants included in this study, there was a mean follow-up of 5.62 years. Driving cessation (8%) was associated with older age, female sex, progression to symptomatic AD (CDR ≥0.5), and poorer performance on a preclinical Alzheimer cognitive composite (PACC) score. Aβ PET imaging did not independently predict driving cessation, whereas CSF biomarkers, specifically t-Tau/Aβ42 (hazard ratio [HR] 2.82, 95% CI 1.23-6.44, p = 0.014) and p-Tau/Aβ42 (HR 2.91, 95% CI 1.28-6.59, p = 0.012) ratios, were independent predictors in the simple model adjusting for age, education, and sex. However, in the full model, progression to cognitive impairment based on the CDR and PACC score across each model was associated with a higher risk of driving cessation, whereas AD biomarkers were not statistically significant. Female sex, CDR progression, and neuropsychological measures of cognitive functioning obtained in the clinic were strongly associated with future driving cessation. The results emphasize the need for early planning and conversations about driving retirement in the context of cognitive decline and the immense value of clinical measures in determining functional outcomes.

A systematic review of the role of TREM2 in Alzheimer's disease.

Given the established genetic linkage between triggering receptors expressed on myeloid cells 2 (TREM2) and Alzheimer's disease (AD), an expanding research body has delved into the intricate role of TREM2 within the AD context. However, a conflicting landscape of outcomes has emerged from both in vivo and in vitro investigations. This study aimed to elucidate the multifaceted nuances and gain a clearer comprehension of the role of TREM2. PubMed database was searched spanning from its inception to January 2022. The search criteria took the form of ("Alzheimer's disease" OR "AD") AND ("transgenic mice model" OR "transgenic mouse model") AND ("Triggering receptor expressed on myeloid cells" OR "TREM2"). Inclusion criteria consisted of the following: (1) publication of original studies in English; (2) utilization of transgenic mouse models for AD research; and (3) reports addressing the subject of TREM2. A total of 43 eligible articles were identified. Our analysis addresses four pivotal queries concerning the interrelation of TREM2 with microglial function, Aβ accumulation, tau pathology, and inflammatory processes. However, the diverse inquiries posed yielded inconsistent responses. Nevertheless, the inconsistent roles of TREM2 within these AD mouse models potentially hinge upon factors such as age, sex, brain region, model type, and detection methodologies. This review substantiates the evolving understanding of TREM2's disease progression-dependent impacts. Furthermore, it reviews the interplay between TREM2 and its effects across diverse tissues and temporal stages.

Behaviour Hallmarks in Alzheimer's Disease 5xFAD Mouse Model.

The 5xFAD transgenic mouse model widely used in Alzheimer's disease (AD) research recapitulates many AD-related phenotypes with a relatively early onset and aggressive age-dependent progression. Besides developing amyloid peptide deposits alongside neuroinflammation by the age of 2 months, as well as exhibiting neuronal decline by the age of 4 months that intensifies by the age of 9 months, these mice manifest a broad spectrum of behavioural impairments. In this review, we present the extensive repertoire of behavioural dysfunctions in 5xFAD mice, organised into four categories: motor skills, sensory function, learning and memory abilities, and neuropsychiatric-like symptoms. The motor problems, associated with agility and reflex movements, as well as balance and coordination, and skeletal muscle function, typically arise by the time mice reach 9 months of age. The sensory function (such as taste, smell, hearing, and vision) starts to deteriorate when amyloid peptide buildups and neuroinflammation spread into related anatomical structures. The cognitive functions, encompassing learning and memory abilities, such as visual recognition, associative, spatial working, reference learning, and memory show signs of decline from 4 to 6 months of age. Concerning neuropsychiatric-like symptoms, comprising apathy, anxiety and depression, and the willingness for exploratory behaviour, it is believed that motivational changes emerge by approximately 6 months of age. Unfortunately, numerous studies from different laboratories are often contradictory on the conclusions drawn and the identification of onset age, making preclinical studies in rodent models not easily translatable to humans. This variability is likely due to a range of factors associated with animals themselves, housing and husbandry conditions, and experimental settings. In the forthcoming studies, greater clarity in experimental details when conducting behavioural testing in 5xFAD transgenic mice could minimise the inconsistencies and could ensure the reliability and the reproducibility of the results.

Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology.

We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices of human brains, which are routinely acquired in brain banks but seldom used for quantitative analysis. Our tools can: (1) 3D reconstruct a volume from the photographs and, optionally, a surface scan; and (2) produce a high-resolution 3D segmentation into 11 brain regions per hemisphere (22 in total), independently of the slice thickness. Our tools can be used as a substitute for ex vivo magnetic resonance imaging (MRI), which requires access to an MRI scanner, ex vivo scanning expertise, and considerable financial resources. We tested our tools on synthetic and real data from two NIH Alzheimer's Disease Research Centers. The results show that our methodology yields accurate 3D reconstructions, segmentations, and volumetric measurements that are highly correlated to those from MRI. Our method also detects expected differences between post mortem confirmed Alzheimer's disease cases and controls. The tools are available in our widespread neuroimaging suite 'FreeSurfer' (https://surfer.nmr.mgh.harvard.edu/fswiki/PhotoTools).

Glucose 6 phosphate dehydrogenase overexpression rescues the loss of cognition in the double transgenic APP/PS1 mouse model of Alzheimer’s disease

Mice models of Alzheimer's disease (APP/PS1) typically experience cognitive decline with age. G6PD overexpressing mice (G6PD-Tg) exhibit better protection from age-associated functional decline including improvements in metabolic and muscle functions as well as reduced frailty compared to their wild-type counterparts. Importantly G6PD-Tg mice show diminished accumulation of DNA oxidation in the brain at different ages in both males and females. To further explore the potential benefits of modulating the G6PD activity in neurodegenerative diseases, triple transgenic mice (3xTg G6PD) were generated, overexpressing APP, PSEN1, and G6PD genes. The cognitive decline characteristic of APP/PS1 mice was prevented in 3xTg G6PD mice, despite similar amyloid-β (Aβ) levels in the hippocampus. This challenges the dominant hypothesis in Alzheimer's disease (AD) etiology and the majority of therapeutic efforts in the field, based on the notion that Aβ is pivotal in cognitive preservation.Notably, the antioxidant properties of G6PD led to a decrease in oxidative stress parameters, such as improved GSH/GSSG and GSH/CysSSG ratios, without major changes in oxidative damage markers. Additionally, metabolic changes in 3xTg G6PD mice increased brain energy status, countering the hypometabolism observed in Alzheimer's models. Remarkably, a higher respiratory exchange ratio suggested increased carbohydrate utilization. The relative failures of Aβ-targeted clinical trials have raised significant skepticism on the amyloid cascade hypothesis and whether the development of Alzheimer's drugs has followed the correct path. Our findings highlight the significance of targeting glucose-metabolizing enzymes rather than solely focusing on Aβ in Alzheimer's research, advocating for a deeper exploration of glucose metabolism's role in cognitive preservation.

Benchmarking of a multi-biomarker low-volume panel for Alzheimer's Disease and related dementia research.

Alzheimer's Disease (AD) biomarker measurement is key to aid in the diagnosis and prognosis of the disease. In the research setting, participant recruitment and retention and optimization of sample use, is one of the main challenges that observational studies face. Thus, obtaining accurate established biomarker measurements for stratification and maximizing use of the precious samples is key. Accurate technologies are currently available for established biomarkers, mainly immunoassays and immunoprecipitation liquid chromatography-mass spectrometry (IP-MS), and some of them are already being used in clinical settings. Although some immunoassays- and IP-MS based platforms provide multiplexing for several different coding proteins there is not a current platform that can measure all the stablished and emerging biomarkers in one run. The NUcleic acid Linked Immuno-Sandwich Assay (NULISA™) is a mid-throughput platform with antibody-based measurements with a sequencing output that requires 15μL of sample volume to measure more than 100 analytes, including those typically assayed for AD. Here we benchmarked and compared the AD-relevant biomarkers including in the NULISA against validated assays, in both CSF and plasma. Overall, we have found that CSF measures of Aß42/40, NfL, GFAP, and p-tau217 are highly correlated and have similar predictive performance when measured by immunoassay, mass-spectrometry or NULISA. In plasma, p-tau217 shows a performance similar to that reported with other technologies when predicting amyloidosis. Other established and exploratory biomarkers (total tau, p-tau181, NRGN, YKL40, sTREM2, VILIP1 among other) show a wide range of correlation values depending on the fluid and the platform. Our results indicate that the multiplexed immunoassay platform produces reliable results for established biomarkers in CSF that are useful in research settings, with the advantage of measuring additional novel biomarkers using minimal sample volume.