Biology subjects

Yoo, S.

Publications and source records attributed to Yoo, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Biogenesis of circular RNAs in vitro and in vivo from the Drosophila Nk2.1/scarecrow gene

scarecrow (scro) encodes a fly homolog of mammalian Nkx2.1 that is vital for early fly development as well as for optic lobe development. Interestingly, scro was reported to produce a circular RNA (circRNA). In this study, we identified 12 different scro circRNAs, which are either mono- or multi-exonic forms. The most abundant forms are circE2 carrying the second exon only and bi-exonic circE3-E4. Levels of circE2 show an age-dependent increase in adult heads, supporting a general trend of high accumulation of circRNAs in aged fly brains. Aligning sequences of introns flanking exons uncovered two pairs of intronic complementary sequences (ICSs); one pair residing in introns 1 and 2 and the other in introns 2 and 4. The first pair was demonstrated to be essential for the circE2 production in cell-based assays; furthermore, deletion of the region including potential ICS components in the intron-2 reduced in vivo production of circE2 and circE3-E4 by 80%, indicating them to be essential for the biogenesis of these isoforms. Besides the ICS, the intron regions immediately abutting exons seemed to be responsible for a basal level of circRNA formation. Moreover, the replacement of scro-ICS with those derived from laccase2 was comparably effective in scro-circRNA production, buttressing the importance of the hairpin-loop structure formed by ICS for the biogenesis of circRNA. Lastly, overexpressed scro affected outcomes of both linear and circular RNAs from the endogenous scro locus, suggesting that Scro plays a direct or indirect role in regulating expression levels of either or both forms.

genetics↗

bioRxiv2023

A High-Throughput Microphysiological Liver Chip System to Model Direct and Idiosyncratic Drug-Induced Liver Injury Using Human Liver Organoids

1.ObjectiveDrug-induced liver injury (DILI) is a major failure mode in pharmaceutical development. This study aims to address the limitations of existing preclinical models by introducing a high-throughput, microfluidic liver-on-a-chip system, termed as "Curio Barrier Liver Chips," seeded with human liver organoids to enable metabolic and phenotypic morphologic characterization. MethodsCurio Barrier liver chips, fabricated in an 8x2 well configuration, were utilized to establish 3D liver organoid cultures. Human-induced pluripotent stem cells (iPSCs) were differentiated into hepatic-like organoids (HLOs), and their viability, liver-specific functions, and pharmacological responses were assessed over 28 days. ResultsThe Curiochips successfully maintained liver physiology and function, showing strong albumin secretion and cytochrome P450 (CYP) activities through 28 days. Unlike traditional models requiring millimolar drug concentrations to detect hepatotoxicity, this platform showed increased sensitivity for APAP and FIAU at micromolar concentrations. In situ differentiation of foregut spheroids to liver organoids was also achieved, further simplifying the establishment of liver chips. Furthermore, the chips demonstrated viability, function and DILI responsiveness for 28 days making this an improved model for studying idiosyncratic DILI with prolonged drug exposure and high-throughput capabilities compared to other available systems or primary human hepatocytes. ConclusionsThe Curiochips offer an advanced, miniaturized in vitro model for early-stage drug development and a sensitive, responsive and cost-effective means to detect direct hepatotoxicity. The high-throughput capability, coupled with robust functionality and pharmacological responses make it a promising tool for improving the prediction and understanding of DILI mechanisms in general and those that required prolonged drug exposure. The model also opens new avenues for research in other chronic liver diseases.

pharmacology and toxicology↗

bioRxiv2023

Design and validation of a high-throughput in vitro model of the outer Blood-Retinal Barrier (oBRB) using the Curiochips Microphysiological System

Numerous diseases, including AMD (age-related macular degeneration), arise from the blood-retinal barrier and blood vessel abnormalities in the eye; unfortunately, there is a lack of reliable in-vitro models for their systematic study. This study describes a high-throughput microphysiological system (MPS) designed to model the outer Blood-Retinal Barrier (oBRB). The MPS platform is engineered to integrate seamlessly with high-content screening technologies, utilizing a design with a single oBRB model incorporating RPE (retina pigment epithelial cells) and endothelial cell co-culture to fit within a single 96-well. Arranged in the standard 96-well plate format, the platform allows high-throughput assessment of barrier integrity through 3D confocal imaging (ZO-1 staining), Trans Epithelial Electrical Resistance (TEER), and permeability measurements. The oBRB model enables the investigation of crosstalk among different cell types in co-culture. This includes assessing changes in the barrier integrity of the Retinal Pigment Epithelium (RPE) monolayer and investigating neovascularization events resulting from endothelial cell remodeling. The platform is positioned for utility in drug discovery and development efforts targeting diseases involving oBRB damage and choroidal neovascularization, such as age-related macular degeneration (AMD).

bioengineering↗

bioRxiv2023

Antibody-based immunotherapy targeting FAM19A5 reverses synaptic loss and improves cognitive function in Alzheimer's disease.

IntroductionAlzheimers disease (AD) is characterized by the dysregulation of synaptic balance, with progressive loss of synapses outpacing formation, ultimately leading to cognitive decline. However, the lack of effective strategies for restoring lost synapses poses a major barrier to improving clinical outcomes. MethodsWe developed NS101, a monoclonal antibody targeting FAM19A5, a brain-secreted protein. Its preclinical efficacy in restoring synapses and cognition was evaluated using APP/PS1 and P301S mice. The clinical safety and target engagement of NS101 were examined in human participants. ResultsFAM19A5 binds to LRRC4B, a postsynaptic adhesion molecule, leading to synapse reduction. Blocking this interaction with NS101 normalized the rate of synapse elimination in AD mice. This synaptic rebalancing restored the number and function of synapses, resulting in improved cognition. Systemically administered NS101 facilitated the transport of brain FAM19A5 into the bloodstream. DiscussionTargeting FAM19A5 may hold clinical promise for treating AD by restoring synaptic balance.

neuroscience↗

bioRxiv2023

FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches

Pregnant females may use medications to manage health problems that develop during pregnancy or that they had prior to pregnancy. However, using medications during pregnancy has a potential risk to the fetus. Assessing the fetotoxicity of drugs is essential to ensure safe treatments, but the current process is challenged by ethical issues, time, and cost. Therefore, the need for in silico models to efficiently assess the fetotoxicity of drugs has recently emerged. Previous studies have proposed successful machine learning models for fetotoxicity prediction and even suggest molecular substructures that are possibly associated with fetotoxicity risks or protective effects. However, the interpretation of the decisions of the models on fetotoxicity prediction for each drug is still insufficient. This study constructed machine learning-based models that can predict the fetotoxicity of drugs while providing explanations for the decisions. For this, permutation feature importance was used to identify the general features that the model made significant in predicting the fetotoxicity of drugs. In addition, features associated with fetotoxicity for each drug were analyzed using the attention mechanism. The predictive performance of all the constructed models was significantly high (AUROC: 0.854-0.974, AUPR: 0.890-0.975). Furthermore, we conducted literature reviews on the predicted important features and found that they were highly associated with fetotoxicity. We expect that our model will benefit fetotoxicity research by providing an evaluation of fetotoxicity risk for drugs or drug candidates, along with an interpretation of that prediction. Author summaryDrugs are often necessary for the treatment of diseases in pregnant females. However, some drugs can potentially cause fetotoxicities, such as teratogenicity and abortion. Therefore, it is essential to study fetotoxicity, but traditional toxicity testing demands time, money, and labor. To modernize these testing methods, in silico approaches for predicting the fetotoxicity of drugs are emerging. The proposed models so far have successfully predicted the fetotoxicity of drugs and proposed some fetotoxicity-related substructures, but the interpretation of the models determination is still insufficient. In this study, we proposed FetoML to predict the fetotoxicity of drugs based on machine learning and provide the substructures that the model focused on in predicting fetotoxicity for each drug. We confirmed the significant predictive performance and interpretability of the model through a quantitative performance evaluation and literature review. We expect FetoML to benefit fetotoxicity studies of drugs by modernizing the paradigm of fetotoxicity testing and providing insights to researchers.

systems biology↗

bioRxiv2023

Generation of Super-resolution Images from Barcode-based Spatial Transcriptomics Using Deep Image Prior

Spatial transcriptomics (ST) has revolutionized the field of biology by providing a powerful tool for analyzing gene expression in situ. However, current ST methods, particularly barcode-based methods, have limitations in reconstructing high-resolution images from barcodes sparsely distributed in slides. Here, we present SuperST, a novel algorithm that enables the reconstruction of dense matrices from low-resolution ST libraries. SuperST based on deep image prior reconstructs spatial gene expression patterns as image matrices. SuperST allows gene expression mapping to better reflect immunofluorescence (IF) images. Compared with previous methods, SuperST generated output images that more closely resembled IF images for given gene expression maps. Additionally, SuperST overcomes the limitations inherent in IF images, highlighting its potential applications in the realm of spatial biology. By providing a more detailed understanding of gene expression in situ, SuperST has the potential to contribute to comprehensively understanding biology from various tissues.

bioinformatics↗

bioRxiv2023

Effects of focused ultrasound in a "clean" mouse model of ultrasonic neuromodulation

Recent studies on ultrasonic neuromodulation (UNM) in rodents have shown that focused ultrasound (FUS) can activate peripheral auditory pathways, leading to off-target and brain-wide excitation, which obscures the direct activation of the target area by FUS. To address this issue, we developed a new mouse model, the double transgenic Pou4f3+/DTR x Thy1-GCaMP6s, which allows for inducible deafening using diphtheria toxin and minimizes off-target effects of UNM while allowing effects on neural activity to be visualized with fluorescent calcium imaging. Using this model, we found that the auditory confounds caused by FUS can be significantly reduced or eliminated within a certain pressure range. At higher pressures, FUS can result in focal fluorescence dips at the target, elicit non-auditory sensory confounds, and damage tissue, leading to spreading depolarization. Under the acoustic conditions we tested, we did not observe direct calcium responses in the mouse cortex. Our findings provide a cleaner animal model for UNM and sonogenetics research, establish a parameter range within which off-target effects are confidently avoided, and reveal the non-auditory side effects of higher-pressure stimulation.

neuroscience↗

bioRxiv2023

Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism

AO_SCPLOWBSTRACTC_SCPLOWAutism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD, and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 47 ASD and 37 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction improvements were marked in transmodal association systems, such as the default mode network, in both controls and ASD. Improvements were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. Regional differences followed a sensory-to-transmodal cortical hierarchy, with an increased gap between groups in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and can help explain its wide range of associated symptoms.

neuroscience↗

bioRxiv2023

GAN-MAT: Generative Adversarial Network-based Microstructural Profile Covariance Analysis Toolbox

AO_SCPLOWBSTRACTC_SCPLOWMultimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community, and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.

neuroscience↗

bioRxiv2023

Multifunctional Materials Strategies for Enhanced Safety of Wireless, Skin-Interfaced Bioelectronic Devices

Many recently developed classes of wireless, skin-interfaced bioelectronic devices rely on conventional thermoset silicone elastomer materials, such as poly(dimethylsiloxane) (PDMS), as soft encapsulating structures around collections of electronic components, radio frequency antennas and, commonly, rechargeable batteries. In optimized layouts and device designs, these materials provide attractive features, most prominently in their gentle, noninvasive interfaces to the skin even at regions of high curvature and large natural deformations. Past work, however, overlooks opportunities for developing variants of these materials for multimodal means to enhance the safety of the devices against failure modes that range from mechanical damage to thermal runaway. This paper presents a self-healing PDMS dynamic covalent matrix embedded with chemistries that provide thermochromism, mechanochromism, strain-adaptive stiffening, and thermal insulation, as a collection of attributes relevant to safety. Demonstrations of this materials system and associated encapsulation strategy involve a wireless, skin-interfaced device that captures mechanoacoustic signatures of health status. The concepts introduced here can apply immediately to many other related bioelectronic devices.

bioengineering↗

bioRxiv2023

Whole-brain structural connectome asymmetry in autism

AO_SCPLOWBSTRACTC_SCPLOWAutism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in 47 individuals with autism and 37 healthy controls using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. We compared the asymmetry index between individuals with autism and neurotypical controls and found atypical structural connectome asymmetry in the sensory, default-mode, and limbic networks and the caudate in autism. Network communication provided topological underpinnings by demonstrating that the temporal and dorsolateral prefrontal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the caudate region in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry is associated with communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.

neuroscience↗

bioRxiv2023

Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps

Interpretation of cryo-electron microscopy (cryo-EM) maps requires building and fitting 3-D atomic models of biological molecules. AlphaFold-predicted models generate initial 3-D coordinates; however, model inaccuracy and conformational heterogeneity often necessitate labor-intensive manual model building and fitting into cryo-EM maps. In this work, we designed a protein modelbuilding workflow, which combines a deep-learning cryo-EM map feature enhancement tool, CryoFEM (Cryo-EM Feature Enhancement Model) and AlphaFold. A benchmark test using 36 cryo-EM maps shows that CryoFEM achieves state-of-the-art performance in optimizing the Fourier Shell Correlations between the maps and the ground truth models. Furthermore, in a subset of 17 datasets where the initial AlphaFold predictions are less accurate, the workflow significantly improves their model accuracy. Our work demonstrates that the integration of modern deep learning image enhancement and AlphaFold may lead to automated model building and fitting for the atomistic interpretation of cryo-EM maps.

bioinformatics↗

bioRxiv2023

Molecular identification of ALDH1A1 and SIRT2 in the astrocytic putrescine-to-GABA metabolic pathway

GABA ({gamma}-aminobutyric acid) is the primary inhibitory neurotransmitter in the CNS. In astrocytes, GABA is synthesized by degradation of putrescine by monoamine oxidase B (MAO-B), a process which is known to mediate tonic inhibition of neuronal excitability. This astrocytic tonic GABA and related enzymes are also reported to be involved in memory impairment in Alzheimers Disease, and therefore are potential therapeutic targets to rescue memory in AD patients. However, the enzymes downstream of MAO-B in this pathway have not been elucidated yet. To fill this gap in knowledge, we performed transcriptomic and literature database analysis and identified Aldehyde dehydrogenase 1 family, member A1 (ALDH1A1) and a histone deacetylase enzyme Sirtuin2 (SIRT2) as plausible candidate enzymes in primary cultured astrocytes. Immunostaining, metabolite analyses, and sniffer patch clamp performed in the presence or absence of suitable inhibitors, or with genetic ablation of the candidate enzymes recapitulated their participation in GABA production. We propose ALDH1A1 and SIRT2 as potential therapeutic targets against Alzheimers Disease.

neuroscience↗

bioRxiv2022

NMY-2, TOE-2 and PIG-1 Regulate C. elegans Asymmetric Cell Divisions

Asymmetric cell division (ACD) is an important mechanism that generates cellular diversity during development. Not only do asymmetric cell divisions produce daughter cells of different fates, many can produce daughters of different sizes, which we refer to as Daughter Cell Size Asymmetry (DCSA). In C. elegans, apoptotic cells are frequently produced by asymmetric divisions that exhibit DCSA, where the smaller daughter dies. We focus here on the divisions of the Q.a and Q.p neuroblasts, which produce apoptotic cells and divide with opposite polarity using both distinct and overlapping mechanisms. The PIG-1/MELK and TOE-2 proteins both regulate DCSA and specify the apoptotic cell fate in both the Q.a and Q.p divisions. In many asymmetric cell divisions, the non-muscle myosin NMY-2 is involved in properly positioning the cleavage furrow to produce daughters of unequal size. It was previously reported that NMY-2 is asymmetrically distributed and required for the DCSA of Q.a but not Q.p. In this study, we examined endogenously tagged reporters of NMY-2, TOE-2, and PIG-1 and found that all were asymmetric at the cortex during both the Q.a and Q.p divisions. TOE-2 and NMY-2 were biased toward the side of the dividing cell that would produce the smaller daughter, whereas PIG-1 was biased toward the side that would produce the larger daughter. We used temperature-sensitive nmy-2 mutants to determine the role of nmy-2 in these divisions and found that these mutants only displayed DCSA defects in the Q.p division. We generated double mutant combinations between the nmy-2 mutations and mutations in toe-2 and pig-1. The nmy-2 mutations did not significantly alter the DCSA of the toe-2 and pig-1 mutants but did alter the fate of the Q.a and Q.p daughters. This finding suggests that NMY-2 functions together with TOE-2 and PIG-1 to regulate DCSA but plays an independent role in specifying the fate of the Q.a and Q.p descendants.

genetics↗

bioRxiv2022

Updated Variant Curation Expert Panel Criteria and Pathogenicity Classifications for 251 Variants for RYR1-related Malignant Hyperthermia Susceptibility

The ClinGen malignant hyperthermia susceptibility (MHS) variant curation expert panel specified the ACMG/AMP criteria for RYR1-related MHS and a pilot analysis of 84 variants was published. We have now classified an additional 251 variants for RYR1-related MHS according to current ClinGen standards and updated the criteria where necessary. Criterion PS4 was modified such that individuals with multiple RYR1 variants classified as pathogenic (P), likely pathogenic (LP) or variant of uncertain significance (VUS) were not considered as providing evidence for pathogenicity. Critera PS1 and PM5 were revised to consider LP variants at the same amino acid residue as providing evidence for pathogenicity at reduced strength. Finally, PM1 was revised such that if PS1 or PM5 are used PM1, if applicable, should be downgraded to supporting. Of the 251 RYR1 variants, 42 were classified as P/LP, 16 as B/LB, and 193 as VUS. The primary driver of 176 VUS classifications was insufficient evidence supporting pathogenicity, rather than evidence against pathogenicity. Functional data supporting PS3/BS3 was identified for only 13 variants. Based on the posterior probabilities of pathogenicity and variant frequencies in gnomAD, we estimated the prevalence of individuals with RYR1-related MHS pathogenic variants to be between 1/300 and 1/1,075, considerably higher than current estimates. We have updated ACMG/AMP criteria for RYR1-related MHS and classified 251 variants. We suggest that prioritization of functional studies is needed to resolve the large number of VUS classifications and allow for appropriate risk assessment. RYR1-related MHS pathogenic variants are likely to be more common than currently appreciated.

genetics↗

bioRxiv2022

Transcriptional circuitry of NKX2-1 and SOX1 defines an unrecognized lineage subtype of small cell lung cancer

RationaleThe current molecular classification of small cell lung cancer (SCLC) based on expression of four lineage transcription factors still leaves its major subtype SCLC-A as a heterogeneous group, necessitating more precise characterization of lineage subclasses. ObjectivesTo refine the current SCLC classification with epigenomic profiles and to identify features of the re-defined SCLC subtypes. MethodsWe performed unsupervised clustering of epigenomic profiles on 25 SCLC cell lines. Functional significance was evaluated by cell growth, apoptosis and xenograft using CRISPR-Cas9-mediated deletion. The specific cistromic profiles by ChIP-seq and its functional transcriptional partners using co-immunoprecipitation followed by mass spectrometry were determined. Rb1fl/flTrp53fl/fl and Rb1fl/flNkx2-1fl/fl mouse models were engineered to explore the function of Nkx2-1 in tumor initiation and differentiation. H3K27ac profiles were analyzed to reveal 6 human SCLC specimen and 20 mice tumors epigenomic landscapes. Measurements and Main ResultsWe identified an epigenomic subclusters of the major SCLC-A subtype, named SCLC-A and SCLC-A{sigma}. SCLC-A was characterized by the presence of a super-enhancer at the NKX2-1 locus, which was observed in human SCLC specimens and a murine SCLC model. We found NKX2-1, a dual lung and neural lineage factor, is uniquely relevant in SCLC-A. We further found maintenance of this neural identity in SCLC-A is mediated by collaborative transcriptional activity with another neuronal transcriptional factor SOX1. ConclusionsWe comprehensively describe an additional epigenomic heterogeneity of the major SCLC-A subtype, and define SCLC-A subtype by the core regulatory circuitry representing NKX2-1 and SOX1 super-enhancers and their functional collaborations to maintain neuronal linage state.

molecular biology↗

bioRxiv2022

Overestimated Polygenic Prediction due to Overlapping Subjects in Genetic Datasets

Recently, polygenic risk score (PRS) has gained significant attention in studies involving complex genetic diseases and traits. PRS is often derived from summary statistics, from which the independence between discovery and replication sets cannot be monitored. Prior studies, in which the independence is strictly observed, report a relatively low gain from PRS in predictive models of binary traits. We hypothesize that the independence assumption may be compromised when using the summary statistics, and suspect an overestimation bias in the predictive accuracy. To demonstrate the overestimation bias in the replication dataset, prediction performances of PRS models are compared when overlapping subjects are either present or removed. We consider the task of Alzheimers disease (AD) prediction across genetics datasets, including the International Genomics of Alzheimers Project (IGAP), AD Sequencing Project (ADSP), and Accelerating Medicine Partnership - Alzheimers Disease (AMP-AD). PRS is computed from either sequencing studies for ADSP and AMP-AD (denoted as rPRS) or the summary statistics for IGAP (sPRS). Two variables with the high heritability in UK Biobank, hypertension, and height, are used to derive an exemplary scale effect of PRS. Based on the scale effect, the expected performance of sPRS is computed for AD prediction. Using ADSP as a discovery set for rPRS on AMP-AD, {Delta}AUC and {Delta}R2 (performance gains in AUC and R2 by PRS) record 0.069 and 0.11, respectively. Both drop to 0.0017 and 0.0041 once overlapping subjects are removed from AMP-AD. sPRS is derived from IGAP, which records {Delta}AUC and {Delta}R2 of 0.051{+/-}0.013 and 0.063{+/-}0.015 for ADSP and 0.060 and 0.086 for AMP-AD, respectively. On UK Biobank, rPRS performances for hypertension assuming a similar size of discovery and replication sets are 0.0036{+/-}0.0027 ({Delta}AUC) and 0.0032{+/-}0.0028 ({Delta}R2). For height, {Delta}R2 is 0.029{+/-}0.0037. Considering the high heritability of hypertension and height of UK Biobank, we conclude that sPRS results from AD databases are inflated. The higher performances relative to the size of the discovery set were observed in PRS studies of several diseases. PRS performances for binary traits, such as AD and hypertension, turned out unexpectedly low. This may, along with the difference in linkage disequilibrium, explain the high variability of PRS performances in cross-nation or cross-ethnicity applications, i.e., when there are no overlapping subjects. Hence, for sPRS, potential duplications should be carefully considered within the same ethnic group.

genomics↗

bioRxiv2021

Astrocytic urea cycle detoxifies Aβ-derived ammonia while impairing memory in Alzheimers Disease

Alzheimers disease (AD) is one of the foremost neurodegenerative diseases, characterized by beta-amyloid (A{beta}) plaques and significant progressive memory loss. In AD, astrocytes are known to take up and clear A{beta} plaques. However, how A{beta} induces pathogenesis and memory impairment in AD remains elusive. We report that normal astrocytes show non-cyclic urea metabolism, whereas A{beta}-treated astrocytes show switched-on urea cycle with upregulated enzymes and accumulated entering-metabolite aspartate, starting-substrate ammonia, end-product urea, and side-product putrescine. Gene-silencing of astrocytic ornithine decarboxylase-1 (ODC1), facilitating ornithine-to-putrescine conversion, boosts urea cycle and eliminates aberrant putrescine and its toxic by-products ammonia, H2O2, and GABA to recover from reactive astrogliosis and memory impairment in AD model. Our findings implicate that astrocytic urea cycle exerts opposing roles of beneficial A{beta} detoxification and detrimental memory impairment in AD. We propose ODC1-inhibition as a promising therapeutic strategy for AD to facilitate removal of toxic molecules and prevent memory loss.

neuroscience↗