Biology subjects

Hong, S.

Publications and source records attributed to Hong, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Mapping protein-exopolysaccharide binding interaction in Staphylococcus epidermidis biofilms by live cell proximity labeling

Bacterial biofilms consist of cells encased in an extracellular polymeric substance (EPS) composed of exopolysaccharides, extracellular DNA, and proteins that are critical for cell-cell adhesion and protect the cells from environmental stress, antibiotic treatments, and the host immune response. Degrading EPS components or blocking their production have emerged as promising strategies for prevention or dispersal of bacterial biofilms, but we still have little information about the specific biomolecular interactions that occur between cells and EPS components and how those interactions contribute to biofilm production. Staphylococcus epidermidis is a leading cause of nosocomial infections as a result of producing biofilms that use the exopolysaccharide poly- (1[->]6)-{beta}-N-acetylglucosamine (PNAG) as a major structural component. In this study, we have developed a live cell proximity labeling approach combined with quantitative mass spectrometry-based proteomics to map the PNAG interactome of live S. epidermidis biofilms. Through these measurements we discovered elastin-binding protein (EbpS) as a major PNAG-interacting protein. Using live cell binding measurements, we found that the lysin motif (LysM) domain of EbpS specifically binds to PNAG present in S. epidermidis biofilms. Our work provides a novel method for the rapid identification of exopolysaccharide-binding proteins in live biofilms that will help to extend our understanding of the biomolecular interactions that are required for bacterial biofilm formation.

microbiology↗

bioRxiv2023

Protein Assembly Modulation: A New Approach to ALS Therapeutics

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease with a complex, multifactorial pathophysiology, most commonly manifest as loss of motor neurons. We introduce a new mechanism of ALS pathogenesis via a novel drug-like small molecule series that targets protein disulfide isomerase (PDI) within a previously unappreciated transient and energy-dependent multi-protein complex. This novel drug was found to have activity in cellular models for both familial and sporadic ALS, as well as in transgenic worms, flies, and mice bearing a diversity of human genes with ALS-associated mutations. These compounds were initially identified as modulators of human immunodeficiency virus (HIV) capsid assembly in cell-free protein synthesis and assembly (CFPSA) systems, with demonstrated antiviral activity in cell culture. Their advancement as ALS-therapeutics, and the subsequent separation of activity against HIV and ALS in chemical subseries through structure-activity-relationship optimization, may provide insights into the molecular mechanisms governing pathophysiology of disordered homeostasis relevant to ALS.

neuroscience↗

bioRxiv2023

PolyGR and polyPR knock-in mice reveal a conserved neuroprotective extracellular matrix signature in C9orf72 ALS/FTD neurons

A GGGGCC repeat expansion in C9orf72 is the most common genetic cause of ALS and FTD (C9ALS/FTD). The presence of dipeptide repeat (DPR) proteins, generated by translation of the expanded repeat, is a major pathogenic feature of C9ALS/FTD pathology, but their most relevant effects in a physiological context are not known. Here, we generated C9orf72 DPR knock-in mouse models characterised by physiological expression of 400 codon-optimised polyGR or polyPR repeats, and heterozygous C9orf72 reduction. (GR)400 and (PR)400 knock-in mice exhibit cortical neuronal hyperexcitability, age-dependent spinal motor neuron loss and progressive motor dysfunction, showing that they recapitulate key features of C9FTD/ALS. Quantitative proteomics revealed an increase in extracellular matrix (ECM) proteins in (GR)400 and (PR)400 spinal cord, with the collagen COL6A1 the most increased protein. This signature of increased ECM proteins was also present in C9ALS patient iPSC-motor neurons indicating it is a conserved feature of C9ALS/FTD. TGF-{beta}1 was one of the top predicted regulators of this ECM signature and polyGR expression in human iPSC-neurons was sufficient to induce TGF-{beta}1 followed by COL6A1, indicating TGF-{beta}1 is one driver of the ECM signature. Knockdown of the TGF-{beta}1 or COL6A1 orthologue in Drosophila dramatically and specifically exacerbated neurodegeneration in polyGR flies, showing that TGF-{beta}1 and COL6A1 protect against polyGR toxicity. Altogether, our physiological C9orf72 DPR knock-in mice have revealed a neuroprotective and conserved ECM signature in C9FTD/ALS.

neuroscience↗

bioRxiv2023

Actin Y53 Phosphorylation Regulates Somatic F-actin Radial Translocation to Promote Neuronal Polarization

How neurons accomplish the growth of an axon, and several dendrites sequentially is a cellular process not well understood. Here, we show that preferential somatic F-actin delivery to neurites inhibits neurite growth during axon formation. Thus, the neurite receiving less somatic F-actin is growing as an axon. During dendrites outgrowth, radial somatic F-actin translocation into all neurites is drastically diminished suggesting that cellular growth is restricted by the somatic F-actin flow into the growing neurites. Mechanistically, we report that radial somatic F-actin translocation is mediated via the Myosin II motor. Pharmacological inhibition of these molecular motors promotes neurite elongation and precludes F-actin translocation into neurites. Moreover, we show that actin phosphorylation at Y53, which promotes F-actin instability, is enriched selectively in some neurite shafts to exclude/minimize translocation of somatic F-actin only into those neurites. Therefore, enrichment of actin pY53 in the neurite shaft correlates with the longer neurite during axon formation. Accordingly, the Kinesin-1 motor domain, which accumulates transiently in neurites of stage 2 neurons and only in the emerging axon of stage 3 neurons, localizes preferentially in the neurite with the increased actin pY53 signal in the neurite shaft. Finally, we demonstrate that microtubule acetylation promotes actin phosphorylation, and these cytoskeleton modifications coexist in the longest neurite that grows as an axon. Collectively, our data support a model in which somatic F-actin translocation into undifferentiated neurites impedes growth counteracted by actin pY53, consequently, supporting neuronal polarization during axon formation.

cell biology↗

bioRxiv2023

Predicting the efficacy of BH3 mimetics through the profiling of multiple protein complexes

BH3 mimetics are protein-protein interaction (PPI) inhibitors that saturate anti-apoptotic proteins in the BCL2 family to induce apoptosis in cancer cells, a prominent example of protein complex-targeting therapies. Despite the remarkable success of the BH3 mimetic ABT-199 in treating hematological malignancies, only a fraction of patients respond to ABT-199 and eventually develop resistance, necessitating the predictive biomarkers for both initial responses and resistance development. We here used the single-molecule pull-down and co-immunoprecipitation platform to quantify more than 20 different types of PPI complexes using [~]1.2x106 cells in total, revealing the rewired status of the BCL2 family PPI network. By comparing the obtained multi-dimensional data with BH3 mimetic efficacies determined ex vivo, we constructed an analysis model for ABT-199 efficacy that designates the BCL2-BAX and BCLxL-BAK complexes as the primary mediators of drug effectiveness and resistance. We then applied this model to assist in therapeutic decision-making for acute myeloid leukemia patients in a prospective manner. Our work demonstrates a capability for the extensive characterization of PPI complexes in clinical specimens, potentially opening a new avenue of precision medicine for protein complex-targeting therapies.

molecular biology↗

bioRxiv2022

An in vivo platform for rebuilding functional neocortical tissue

Recent progress in cortical stem cell transplantation has demonstrated its potential to repair the brain. However, current transplant models have yet to demonstrate that the circuitry of transplant-derived neurons can encode useful function to the host. This is likely due to missing cell types within the grafts, abnormal proportions of cell types, abnormal cytoarchitecture, and inefficient vascularization. Here, we devised a transplant platform for testing neocortical tissue prototypes. Dissociated mouse embryonic telencephalic cells in a liquid scaffold were transplanted into aspiration-lesioned adult mouse cortices. The donor neuronal precursors differentiated into upper and deep layer neurons that exhibited synaptic puncta, projected outside of the graft to appropriate brain areas, became electrophysiologically active within one month post-transplant, and responded to visual stimuli. Interneurons and oligodendrocytes were present at normal densities in grafts. Grafts became fully vascularized by 1-week post-transplant and vessels in grafts were perfused with blood. With this paradigm, we could also organize cells into layers. Overall, we have provided proof of concept for an in vivo platform that can be used for developing and testing neocortical-like tissue prototypes.

neuroscience↗

bioRxiv2022

Epigenetic and Signaling Determinants of Blood-Brain Barrier-Regulatory Genetic Networks

The blood-brain barrier (BBB) controls the movement of molecules into and out of the central nervous system (CNS). Since a functional BBB forms by mouse embryonic day E15.5, we reasoned that gene cohorts expressed in CNS endothelial cells (EC) at E13.5 contribute to BBB formation. In contrast, adult gene signatures reflect BBB maintenance mechanisms. Supporting this hypothesis, transcriptomic analysis revealed distinct cohorts of EC genes involved in BBB formation and maintenance. Here, we demonstrate that epigenetic regulators histone deacetylase 2 (HDAC2) and polycomb repressive complex 2 (PRC2) control EC gene expression for BBB development and prevent Wnt/{beta}-catenin (Wnt) target genes from being expressed in adult CNS ECs. Low Wnt activity during development modifies BBB genes epigenetically for the formation of functional BBB. As a Class-I HDAC inhibitor induces adult CNS ECs to regain Wnt activity and BBB genetic signatures that support BBB formation, our results inform strategies to promote BBB repair.

neuroscience↗

bioRxiv2022

FcRγ- NK cell induction by specific CMV and expansion by subclinical viral infections in rhesus macaques

Long-lived memory-like NK cells, characterized by FcR{gamma}-deficiency and enhanced responsiveness to antibody-bound virus-infected cells, have been found in certain human cytomegalovirus (HCMV)-seropositive individuals. Because humans are exposed to numerous microbes and environmental agents, specific relationships between HCMV and FcR{gamma}-deficient NK cells (also known as g-NK cells) have been challenging to define. Here, we show that a subgroup of rhesus cytomegalovirus (RhCMV)-seropositive macaques possesses FcR{gamma}-deficient NK cells that stably persist and display phenotype resembling human FcR{gamma}-deficient NK cells. Moreover, these macaque NK cells resembled human FcR{gamma}-deficient NK cells with respect to functional characteristics, including enhanced responsiveness to RhCMV-infected target in an antibody-dependent manner and hypo-responsiveness to tumor and cytokine stimulation. These cells were not detected in specific-pathogen-free (SPF) macaques free of RhCMV and six other viruses; however, experimental infection of SPF animals with RhCMV strain UCD59, but not RhCMV strain 68-1 or SIV, led to induction of FcR{gamma}-deficient NK cells. In non-SPF macaques, co-infection by RhCMV with other common viruses was associated with higher frequencies of FcR{gamma}-deficient NK cells. These results support a causal role for specific cytomegalovirus strain(s) in the induction of FcR{gamma}-deficient NK cells, and suggest that co-infection by other viruses further expands this memory-like NK cell pool.

immunology↗

bioRxiv2022

Microglia Detect Externalized Phosphatidylserine on Synapses for Elimination via TREM2 in Alzheimer's Disease Models

Genetic studies implicate phagocytosis pathways in microglia to be a major Alzheimers disease (AD)-associated process. Microglia phagocytose synapses in AD mouse models, suggesting a role for microglia in region-specific synapse loss, a pathological hallmark of AD. However, whether specific synapses are targeted for elimination, and if so, how, remains to be elucidated. Here, we show that synapses externalize phosphatidylserine (PtdSer) upon challenge by {beta}-amyloid oligomers, which are then selectively engulfed by microglia. Mechanistically, we find that Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) is critical for microglia to sense and preferentially engulf AD synapses. In brains of mice and humans, TREM2 dysfunction leads to exacerbation of apoptotic synapses. Our work altogether suggests a fundamental role for microglia as brain-resident macrophages to remove damaged synapses in AD. We provide mechanistic insight into how TREM2 variants associated with increased risk of developing AD may contribute to defective microglia-synapse function. One-Sentence summaryMicroglia selectively engulf synapses in Alzheimer-like mouse brains via PtdSer-TREM2 signaling.

neuroscience↗

bioRxiv2022

Perivascular SPP1 Mediates Microglial Engulfment of Synapses in Alzheimers Disease Models

Microglia are phagocytes of the brain parenchyma, where they interact with neurons to engulf synapses in a context-dependent manner. Genetic studies in Alzheimers disease (AD) highlight dysfunctional phagocytic signaling in myeloid cells as disease-associated pathway. In AD models, there is a region-specific reactivation of microglia-synapse phagocytosis involving complement; however, what drives microglia-synapse engulfment remains unknown. Here, we show that SPP1 (Osteopontin), a glycoprotein associated with inflammation, is regionally upregulated and modulates microglial synaptic engulfment in AD mouse models. Ultrastructural examination revealed SPP1 expression predominantly by perivascular macrophages, a subtype of border-associated macrophages, in the hippocampus of mice and patient tissues. Cell-cell interaction networks of single-cell transcriptomics data suggested that perivascular SPP1 drives microglial functional states in the hippocampal microenvironment of AD mice. Absence of Spp1 expression resulted in failure of microglia to mediate synaptic phagocytosis. This study suggests a critical role for perivascular SPP1 in neuroimmune crosstalk in AD-relevant context.

neuroscience↗

bioRxiv2022

Neuron-specific protein network mapping of autism risk genes identifies shared biological mechanisms and disease relevant pathologies

Manuscript summaryThere are hundreds of risk genes associated with autism spectrum disorder (ASD), but signaling networks at the protein level remain unexplored. We use neuron-specific proximity-labeling proteomics (BioID) to identify protein-protein interaction (PPI) networks for 41 ASD-risk genes. Neuron-specific PPI networks, including synaptic transmission proteins, are disrupted by de novo missense variants. The PPI network map reveals convergent pathways, including mitochondrial/metabolic processes, Wnt signaling, and MAPK signaling. CRISPR knockout reveal an association between mitochondrial activity and ASD-risk genes. The PPI network shows an enrichment of 112 additional ASD-risk genes and differentially expressed genes from post-mortem ASD patients. Clustering of risk genes based on PPI networks identifies gene groups corresponding to clinical behavior score severity. Our data reveal that cell type-specific PPI networks can identify individual and convergent ASD signaling networks, provide a method to assess patient variants, and reveal biological insight into disease mechanisms and sub-cohorts of ASD.

neuroscience↗

bioRxiv2022

Multidimensional cerebellar computations for flexible kinematic control of movements

Both the environment and our body keep changing dynamically. Hence, ensuring movement precision requires adaptation to multiple demands occurring simultaneously. Here we show that the cerebellum performs the necessary multi-dimensional computations for the flexible control of different movement parameters depending on the prevailing context. This conclusion is based on the identification of a manifold-like activity in both mossy fibers (MF, network input) and Purkinje cells (PC, output), recorded from monkeys performing a saccade task. Unlike MFs, the properties of PC manifolds developed selective representations of individual movement parameters. Error feedback-driven climbing fiber input modulated the PC manifolds to predict specific, error type-dependent changes in subsequent actions. Furthermore, a feed-forward network model that simulated MF-to-PC transformations revealed that amplification and restructuring of the lesser variability in the MF activity is a pivotal circuit mechanism. Therefore, flexible control of movement by the cerebellum crucially depends on its capacity for multi-dimensional computations.

neuroscience↗

bioRxiv2021

ABCnet : Self-Attention based Atom, Bond Message Passing Network for Predicting Drug-Target Interaction

Drug-target interaction (DTI) is a methodology for predicting the binding affinity between a compound and a target protein, and a key technology in the derivation of candidate substances in drug discovery. As DTI experiments have progressed for a long time, a substantial volume of chemical, biomedical, and pharmaceutical data have accumulated. This accumulation of data has occurred contemporaneously with the advent of the field of big data, and data-based machine learning methods could significantly reduce the time and cost of drug development. In particular, the deep learning method shows potential when applied to the fields of vision and speech recognition, and studies to apply deep learning to various other fields have emerged. Research applying deep learning is underway in drug development, and among various deep learning models, a graph-based model that can effectively learn molecular structures has received more attention as the SOTA in experimental results were achieved. Our study focused on molecular structure information among graph-based models in message passing neural networks. In this paper, we propose a self-attention-based bond and atom message passing neural network which predicts DTI by extracting molecular features through a graph model using an attention mechanism. Model validation experiments were performed after defining binding affinity as a regression and classification problem: binary classification to predict the presence or absence of binding to the drug-target, and regression to predict binding affinity to the drug-target. Classification was performed with BindingDB, and regression was performed with the DAVIS dataset. In the classification problem, ABCnet showed higher performance than MPNN, as it does in the existing study, and in regression, the potential of ABCnet was checked compared to that of SOTA. According to experiments, for Binary classification ABCnet have an average performance improvement of 1% for higher performance on DTI task than other MPNN and for regresssion ABCnet have CI with an average 0.01 to 0.02 performance degradation compared to SOTA. https://www.overleaf.com/project/618a05533676801d8f68ccf6

bioinformatics↗

bioRxiv2021

Massively Parallel Selection of NanoCluster Beacons

NanoCluster Beacons (NCBs) are multicolor silver nanocluster probes whose fluorescence can be activated or tuned by a proximal DNA strand called the activator. While a single-nucleotide difference in a pair of activators can lead to drastically different activation outcomes, termed the polar opposite twins (POTs), it is difficult to discover new POT-NCBs using the conventional low-throughput characterization approaches. Here we report a high-throughput selection method that takes advantage of repurposed next-generation-sequencing (NGS) chips to screen the activation fluorescence of [~]40,000 activator sequences. We find the nucleobases at positions 7-12 of the 18-nucleotide-long activator are critical to creating bright NCBs and positions 4-6 and 2-4 are hotspots to generate yellow and red POTs, respectively. Based on these findings, we propose a "zipper bag model" that explains how these hotspots lead to the creation of distinct silver cluster chromophores and contribute to the difference in chromophore chemical yields. Combining high-throughput screening with machine learning algorithms, we establish a pipeline to rationally design bright and multicolor NCBs.

bioengineering↗

bioRxiv2021

Intravital imaging of cerebral microinfarct reveals an astrocyte reaction led to glial scar

Cerebral microinfarct increases the risk of dementia. But how microscopic cerebrovascular disruption affects the brain tissue in cellular-level are mostly unknown. Herein, with a longitudinal intravital imaging, we serially visualized in vivo dynamic cellular-level changes in astrocyte, pericyte and neuron as well as microvascular integrity after the induction of cerebral microinfarction for 1 month in mice. At day 2-3, it revealed a localized edema with acute astrocyte loss, neuronal death, impaired pericyte-vessel coverage and extravascular leakage indicating blood-brain barrier (BBB) dysfunction. At day 5, edema disappeared with recovery of pericyte-vessel coverage and BBB integrity. But brain tissue continued to shrink with persisted loss of astrocyte and neuron in microinfarct until 30 days, resulting in a collagen-rich fibrous scar surrounding the microinfarct. Notably, reactive astrocytes appeared at the peri-infarct area early at day 2 and thereafter accumulated in the peri-infarct. Oral administration of a reversible monoamine oxidase B inhibitor significantly decreased the astrocyte reactivity and fibrous scar formation. Our result suggests that astrocyte reactivity may be a key target to alleviate the impact of microinfarction.

neuroscience↗

bioRxiv2021

AI-driven high-throughput automation of behavioral analysis and dual-channel wireless optogenetics for multiplexing brain dynamics

Advances in behavioral optogenetics are limited by the absence of high-throughput pipelines for the automated analysis of behavior in freely behaving animals. Although a variety of AI algorithms has been proposed that enable automation of behavioral analysis, existing methods are generally low-throughput. In addition, optogenetic manipulation of neural circuits typically requires physical tethers to light sources, which limits the number of brain areas that can be targeted and thus constrains behavioral testing. Here, we develop a new wireless platform that combines a battery-free dual-channel optogenetic implant with an AI algorithm for high-throughput behavioral analysis. In our platform, a customized AI algorithm detected and quantified freezing behavior of rats that had undergone fear conditioning. Notably, our platform allows up to four enclosures to be monitored simultaneously. Wireless dual-channel optogenetic devices were implanted in the basolateral amygdala (BLA) to permit independent modulation of BLA principal neurons (red light, AAV-CaMKII-JAWS) or BLA interneurons (blue light, AAV-mDlx-ChR2) in freely behaving animals. In vivo validation with behaving rats demonstrates the utility of the telemetry system for large-scale optogenetic studies. SignificanceAI algorithms can enable automation of behavioral analysis and thereby facilitate the progress on behavioral optogenetics. Successful integration of advanced wireless dual-channel optoelectronic devices with biological systems can also yield new tools and techniques for neuroscience research, particularly in the context of techniques for optogenetics. Here, we propose a new approach that combines an advanced AI algorithm with a low power wireless telemetry system, yielding powerful capabilities in the understanding of brain functions and the evaluation of the behavioral consequences of neural circuit manipulations. In vivo studies using optimized systems demonstrate high-throughput automation of behavioral manipulation and analysis via AI-powered wireless telemetry.

neuroscience↗

bioRxiv2021

LBH is a cancer stem cell- and metastasis-driving oncogene essential for WNT stem cell function in breast cancer

Cancer stem cells (CSCs) initiate tumors, resist treatment, and seed lethal metastases; yet CSC-specific treatments are lacking. Aggressive, treatment-resistant triple-negative breast cancers (TNBC) exhibit WNT pathway activation and are CSC enriched. Here, we show that Limb-Bud- and-Heart (LBH), a WNT/{beta}-catenin target required for normal mammary stem cell self-renewal, marks poor prognosis, stem-like TNBC, and is a key controller of breast cancer stemness. LBH is specifically expressed in tumor-initiating CD44+CD24-/low breast CSCs. LBH overexpression confers stem-like, metastatic traits on both TNBC and luminal origin, non-TNBC breast cancer cells by activating stem cell transcriptional programs. Importantly, silencing LBH potently suppresses tumor initiation and metastasis in vivo, and sensitizes TNBC cells to chemotherapy. LBH knockout in the MMTV-Wnt1 breast cancer mouse model, furthermore, revealed LBH is required for WNT-driven breast CSC expansion. Our findings identify LBH as an essential CSC driver downstream of WNT, and a new molecular target for anti-cancer stem cell therapy.

cancer biology↗

bioRxiv2021

MRI Radiomic Signature of White Matter Hyperintensities Is Associated with Clinical Phenotypes

IntroductionNeuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of describing the texture of conventional images beyond what meets the naked eye, radiomic analyses hold potential for evaluating brain health. We sought to: 1) evaluate this novel approach to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and 2) uncover associations between predictive radiomic features and patients clinical phenotypes. MethodsOur analyses were based on a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images and corresponding deep-learning-generated total brain and WMH segmentation. Radiomic features were extracted from normal-appearing brain tissue (brain mask-WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with the most stable selected features predictive of WMH burden and then related this signature to clinical variables (age, sex, hypertension (HTN), atrial fibrillation (AF), diabetes mellitus (DM), coronary artery disease (CAD), and history of smoking) using canonical correlation analysis. ResultsRadiomic features were highly predictive of WMH burden (R2=0.855{+/-}0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p-valuesCV1-6<.001, p-valueCV7=.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and DM, CV4 by HTN, CV5 by AF and DM, CV6 by CAD, and CV7 by CAD and DM. ConclusionRadiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes. Further research could evaluate radiomics to predict the progression of WMH. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe did a systematic review on PubMed until December 1, 2020, for original articles and reviews in which radiomics were used to characterize stroke or cerebrovascular diseases. Radiomic analyses cover a broad ensemble of high-throughput quantification methods applicable to digitalized medical images that extract high-dimensional data by describing a given region of interest by its size, shape, histogram, and relationship between voxels. We used the search terms "radiomics" or "texture analysis", and "stroke", "cerebrovascular disease", "small vessel disease", or "white matter hyperintensities". Our research identified 24 studies, 18 studying radiomics of stroke lesions and 6 studying cerebrovascular diseases. All the latter six studies were based on MRI (T1-FLAIR, dynamic contrast-enhanced imaging, T1 & T2-FLAIR, T2-FLAIR post-contrast, T2-FLAIR, and T2-TSE images). Four studies were describing small vessel disease, and two were predicting longitudinal progression of WMH. The average sample size was small with 96 patients included (maximum: 204). One study on 141 patients identified 7 T1-FLAIR radiomic features correlated with cardiovascular risk factors (age and hyperlipidemia) using univariate correlations. All studies were monocentric and performed on a single MRI scanner. Added value of this studyTo date and to the best of our knowledge, this is the largest radiomics study performed on cerebrovascular disease or any topic, and one of the very few to include a great diversity of participating sites with diverse clinical MRI scanners. This study is the first one to establish a radiomic signature of WMH and to interpret its relationship with common cardiovascular risk factors. Our findings add to the body of evidence that damage caused by small vessel disease extend beyond the visible white matter hyperintensities, but the added value resides in the detection of that subvisible damage on routinely acquired T2-FLAIR imaging. It also suggests that cardiovascular phenotypes might manifest in distinct textural patterns detectable on conventional clinical-grade T2-FLAIR images. Implications of all the available evidenceAssessing brain structural integrity has implications for treatment selection, follow-up, prognosis, and recovery prediction in stroke patients but also other neurological disease populations. Measuring cerebral parenchymal structural integrity usually requires advanced imaging such as diffusion tensor imaging or functional MRI. Translation of those neuroimaging biomarkers remains uncommon in clinical practice mainly because of their time-consuming and costly acquisition. Our study provides a potential novel solution to assess brains structural integrity applicable to standard, routinely acquired T2-FLAIR imaging. Future research could, for instance, benchmark this radiomics approach against diffusion or functional MRI metrics in the prediction of cognitive or functional outcomes after stroke.

neuroscience↗