Biology subjects

Cho, K.

Publications and source records attributed to Cho, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Using XCiMS to Quantify the Benefits of Ion Mobility Spectrometry for Untargeted Metabolomics

Integrating ion mobility spectrometry (IMS) with liquid chromatography-mass spectrometry (LC-MS) has the potential to improve untargeted metabolomics workflows, but assessing the benefits of IMS has been challenging due to a paucity of software solutions to process raw LC-IMS-MS data in a manner that enables direct comparison with LC-MS data. We developed the XCiMS software to collapse 4D data into pseudo-3D data. Peak detection is then performed in the pseudo-3D space, followed by targeted extraction of 4D signals from 3D-guided regions of interest. Here, we applied XCiMS to estimate the potential of IMS for untargeted metabolomics when analyzing human plasma. First, we assessed the number of metabolites that are uniquely resolved by LC-IMS-MS but not LC-MS. Although as many as 50% of 3D peaks produce multiple 4D peaks when using high-resolution IMS, few represent newly resolved structural isomers. We found that the increase in features due to IMS was mostly caused by charge isomers and ion clusters. Second, we investigated the impact of IMS on metabolite identification. When using a 16-minute chromatographic separation, we found that IMS can decrease the frequency of chimeric MS/MS by about half. We conclude that while IMS adds considerable complexity to untargeted metabolomics data without resolving a large number of additional structural isomers relative to a standard LC-MS experiment, it does facilitate metabolite identification by decreasing chimeric spectra and providing CCS values for library searching.

bioinformatics↗

bioRxiv2026

Diverse stresses converge on bacterial periplasmic expansion through distinct physiological mechanisms

Diverse environmental and antibiotic stresses induce localized periplasmic expansion, the separation of the inner membrane from the cell wall and outer membrane, in Gram-negative bacteria, yet whether these morphologically similar responses arise through a common mechanism remains unclear. Here, we compare periplasmic expansion induced by sudden starvation, ciprofloxacin, mitomycin C, and globomycin in Escherichia coli. We find that these perturbations produce similar morphologies through distinct physiological and mechanical routes. Ciprofloxacin- and mitomycin C-induced periplasmic expansion coincides with loss of turgor, whereas starvation requires water efflux, and globomycin leads to unequal expansion of the inner and outer membrane as a result of aberrant inner membrane-cell wall crosslinking. Outer membrane stiffness modulates expansion during ciprofloxacin treatment. Despite these distinct mechanisms, robust periplasmic expansion during starvation and treatment with ciprofloxacin or globomycin requires UDP-glucose synthesis. Together, these findings establish periplasmic expansion as a convergent physical outcome of diverse stresses and reveal the remarkable plasticity of the Gram-negative cell envelope.

microbiology↗

bioRxiv2026

Evaluation of the Translational Readiness of Pluripotent Stem Cell-Derived Vascular Cell Therapy for Limb Ischemia: A Systematic Review and Meta-analysis

Background: For the first time, pluripotent stem cell (PSC)-derived endothelial cells were administered to a human for peripheral artery disease (PAD), in August 2026. This translation is based on a large preclinical literature claiming that donor cells build blood vessels in animal models of limb ischemia, but whether it supports that claim has not been assessed systematically. Methods: In this systematic review and meta-analysis, we searched MEDLINE, Web of Science, Europe PMC, and Embase to August 2026 for studies of PSC-derived vascular cells in animal models of limb ischemia with an acellular control. Limb perfusion at each experiment's primary timepoint was pooled as Hedges' g in a three-level random-effects model with cluster-robust variance. Donor-cell fate and a seven-level ordinal of vascular contribution were graded for every study. This meta-analysis was registered on PROSPERO (CRD420261465308). Results: Sixty-eight studies in 69 reports met the criteria; 51 contributed 114 comparisons at primary timepoints. Cell therapy increased perfusion (Hedges' g 2.26, 95% CI 1.72-2.79; P=4.1x10-11; I2=87.5%; 95% prediction interval -1.47 to 5.98). No prespecified moderator survived Holm-Bonferroni adjustment, including the donor-cell fate grade (P=0.30). A donor cell was resolved in a vessel wall in 35 studies, and flow through such a vessel in 7. Small-study effects were strong (Egger t=6.25, P=9x10-8) but were not reproduced by a sample-size-based test (P=0.80); trim-and-fill moved the estimate to 1.15. On the natural scale, treated limbs recovered about twice the control perfusion (ratio of means 1.96, 95% CI 1.66-2.33). Limb preservation favored cell therapy in 11 studies with countable events (risk ratio 4.88, 95% CI 2.28-10.45), but 43 of 68 studies reported no functional outcome, and only 22 comparisons from 8 studies were both randomized and blindly assessed. In a post hoc analysis that did not survive multiplicity adjustment, effects were largest in studies whose images could not resolve their incorporation claims (g 3.23) versus those that resolved incorporation (g 2.33). Conclusions: PSC-derived vascular cell therapy improved limb perfusion in animal models, consistently across every sensitivity analysis, although the magnitude is uncertain given heterogeneity and small-study effects. Benefit was not associated with the degree of donor-cell incorporation across studies and was largest where incorporation was least resolvable, a pattern more consistent with reporting and measurement bias than with a true mechanistic effect. The first rigorous, blinded test of that benefit may come not from animals but from the patients now receiving these cells.

cell biology↗

bioRxiv2026

Reprogramming VHL with molecular glues enables selective degradation of caspase-2

Molecular glue degraders (MGDs) reprogram E3 ligases to eliminate neosubstrates, yet their application has largely been confined to CRBN. Here, we identify caspase-2 as a new neosubstrate for von Hippel-Lindau (VHL), expanding the scope of VHL-based MGDs. Guided by a focused VHL ligand library design, we employed TurboID-based proximity labeling to discover stereoisomeric compounds (dCASP2-1 and dCASP2-2) that selectively recruit caspase-2 to VHL and promote its ubiquitin-proteasome system-dependent degradation. Further structure-activity relationship (SAR) studies yielded dCASP2-3 and dCASP2-4, which enhanced degradation potency (by 622-fold relative to dCASP2-1) and abolished enantioselectivity. Mechanistic mapping localized the degrader-induced interface to a two-helix region of the caspase-2 CARD domain, with residues H33, P34, and D100 essential for VHL engagement. Degron-guided computational modeling of the VHL/MGD/caspase-2 ternary complex provided structural insight into neosubstrate recognition. Together, we report the development of VHL molecular glues that selectively and potently degrade caspase-2, offering chemical probes to interrogate its functions in apoptosis and stress responses, while broadening the substrate landscape of VHL-based MGDs.

biochemistry↗

bioRxiv2026

Sustained loss of Pptc7 triggers variable skeletal muscle dysfunction and diminished body mass through dysregulation of BNIP3

The mitochondrial phosphatase PPTC7 is required to sustain mammalian metabolism, as its global knockout (KO) triggers hypoketotic hypoglycemia and perinatal lethality in mice. However, the extent to which the loss of Pptc7 manifests pathology beyond the perinatal transition is unknown. Furthermore, PPTC7 was recently identified as dual functional, regulating mitochondrial protein phosphorylation and receptor mediated mitophagy, rendering it unclear which function(s) may influence in vivo physiology. Here, we find that sustained, inducible Pptc7 KO decreased lean mass, compromised whole body oxygen consumption, and altered circulating metabolites in adult male mice. We hypothesized that these phenotypes stemmed from skeletal muscle dysfunction and found lower mass and fiber cross-sectional area with shifts in fiber type distribution in select muscles of the hindlimb in Pptc7 KO animals. Loss of PPTC7 increased BNIP3 protein levels and decreased mitochondrial content in skeletal muscle, suggesting elevated mitophagy may drive pathology. Consistently, KO of Bnip3 rescued the lower body weight and lean mass seen in inducible Pptc7 KO adult animals and partially rescued perinatal lethality in global Pptc7 KO mice. These data demonstrate that loss of PPTC7 incites surprisingly variable dysfunction across physiological contexts that at least partially stems from dysregulated BNIP3.

physiology↗

bioRxiv2026

The MIRO1-BAX Complex Dictates Life and Death at the Mitochondrial Gate

BAX macropores in the outer mitochondrial membrane (OMM) are canonical mediators of apoptosis, but whether the same pore structure can drive distinct cell death pathways remains unclear. Here, we identify the OMM protein MIRO1 as a context-specific modulator of BAX activity. Mechanistically, MIRO1 binds BAX via MIRO1s N-terminal domain to promote macropore formation and the release of mitochondrial DNA (mtDNA) into the cytoplasm, triggering the STING-pIRF3 signaling axis. In glioma cells, this pathway sustains GPX4 expression via pIRF3-mediated transcriptional activation and confers ferroptosis resistance while bypassing inflammation. By contrast, in Parkinsonian neurons, the MIRO1-BAX complex promotes mitochondrial-stress-induced apoptosis. Using structure-guided drug discovery, we developed first-in-class small molecules that allosterically disrupt the MIRO1-BAX complex by engaging MIRO1s distal GTPase pocket. These compounds sensitize glioma cells to ferroptosis and protect neurons from apoptosis. Our findings reveal a disease-specific mitochondrial switch for life-death decisions and illuminate the molecular logic by which cells exploit and interpret OMM permeabilization.

Cell Biology↗

bioRxiv2026

Cell-specific isotope labeling identifies myo-inositol transfer between neurons and oligodendroglia to support myelin repair

Neurons and glial cells are biochemically coupled through the exchange of nutrients, but our knowledge of which metabolites are transferred between them remains limited due to technical challenges. Here, we introduce a strategy to label specific cell types with isotopic tracers so that metabolite transfer can be measured directly in the intact brain. By engineering neurons in mice to metabolize 13C-labeled cellobiose, a glucose dimer that wild-type cells cannot catabolize, we selectively track neuron-derived metabolites by using mass spectrometry-based metabolomics. Applying this approach enabled us to identify myo-inositol as a critical metabolite synthesized by neurons and transferred to oligodendrocyte progenitor cells (OPCs) via the SLC5A3 transporter. The transfer of myo-inositol from neurons to OPCs promotes OPC proliferation and differentiation by enhancing phosphatidylinositol synthesis and upregulating expression of myelin-associated genes. During demyelination, deficient nutrient transfer can be rescued by dietary supplementation of myo-inositol, which accelerates myelin repair. These findings establish a generalizable technology for tracing intercellular metabolite transfer in vivo and identify a previously unrecognized mechanism of myo-inositol transfer from neurons to glial cells in support of CNS regeneration, revealing a potential metabolic target for therapeutic intervention in neurodegenerative disease.

biochemistry↗

bioRxiv2026

Detecting Manuscripts Related to Computable Phenotypes Using a Transformer-based Language Model

ObjectiveThe demand for a comprehensive phenomics library, which requires identifying computable phenotype definitions and associated metadata from an ever-expanding biomedical literature, presents a significant, labor-intensive, and unscalable challenge. To address this, we introduce a transformer-based language model specifically designed for identifying biomedical texts containing computable phenotypes and piloted its use in the Centralized Interactive Phenomics Resource (CIPHER) platform. Materials and MethodsWe fine-tuned a BioBERT model using a labeled dataset of 396 manuscripts. The model incorporates our novel sliding-window approach to effectively overcome token-length limitations, thereby enabling accurate classification of full-length manuscripts. For scalable deployment and continuous refinement, we developed a cohesive framework that integrates a web-based user interface, a control server, and a classification module. ResultsThe staged approach for model development yielded a final model with 95% accuracy. The web-based user interface was deployed on the CIPHER platform and enables user feedback for model retraining. DiscussionWe developed a model and user interface which are currently in use by data curators to identify computable phenotype definitions from the literature. ConclusionThrough this system, users can submit literature, assess classification results, and provide feedback directly influencing future model training, thereby offering an efficient and adaptive solution for accelerating phenotype-driven literature curation.

bioinformatics↗

bioRxiv2026

MassID provides near complete annotation of metabolomics data with identification probabilities

Liquid chromatography coupled to mass spectrometry (LC/MS) is a powerful tool in metabolomics research, generating tens-of-thousands of signals from a single biological sample. However, current software solutions for unbiased assessment of metabolomics data analysis are limited by complex sources of noise and non-quantitative metabolite identifications that make results difficult to interpret. Here, we present MassID, a cloud-based untargeted metabolomics pipeline that aims to overcome the innate challenges of unbiased metabolite analysis and perform end-to-end data processing, transforming raw spectra to normalized and identified metabolite profiles. MassID incorporates a suite of software functionalities, including deep learning-based peak detection and comprehensive noise filtering. In addition, with MassID we introduce a novel software module: DecoID2 that enables probabilistic metabolite identification for false discovery rate (FDR)-controlled metabolomics. When applied to a human plasma dataset, MassID results in near-complete signal annotation, identification of >4,000 metabolites (including >1,200 compounds at an FDR <5%) across four complementary LC/MS runs, and enables integrated downstream analyses to understand biochemical dysregulation at both the molecular and pathway level. When compared to the Metabolomics Standards Initiative (MSI) confidence levels, identification probability generally correlated with MSI levels. However, only 356/418 of MSI Level 1 compounds were identified with <5% FDR and the remaining 884 FDR < 5% compounds were identified from MSI L2-L3 compounds, highlighting the enhanced specificity and discovery potential achieved by MassID.

bioinformatics↗

bioRxiv2026

SLC33A1 exports oxidized glutathione to maintain endoplasmic reticulum redox homeostasis

The endoplasmic reticulum (ER) requires an oxidative environment to support the efficient maturation of secretory and membrane proteins. This is in part established by glutathione, a redox-active metabolite present in reduced (GSH) and oxidized (GSSG) forms. The ER maintains a higher GSSG:GSH ratio than the cytosol; however, the mechanisms controlling ER redox balance remain poorly understood. To address this, we developed a method for the rapid immunopurification of the ER, enabling comprehensive profiling of its proteome and metabolome. Combining this approach with CRISPR screening, we identified SLC33A1 as the major ER GSSG exporter in mammalian cells. Loss of SLC33A1 leads to GSSG accumulation in the ER and a liposome-based assay demonstrates that SLC33A1 directly transports GSSG. Cryo-EM structures and molecular dynamics simulations reveal how SLC33A1 binds GSSG and identify residues critical for its transport. Finally, an imbalance in GSSG:GSH ratio induces ER stress and dependency on the ER-associated degradation (ERAD) pathway, driven by a shift in protein disulfide isomerases (PDIs) toward their oxidized forms. Altogether, our work establishes SLC33A1-mediated GSSG export as a key mechanism for ER redox homeostasis and protein maturation.

cell biology↗

bioRxiv2025

A MYC Family Switch: L-MYC Drives and Maintains Neuroendocrine Lineage Programs in Prostate Cancer

Neuroendocrine prostate cancer (NEPC) is an aggressive, therapy-resistant subtype that emerges through lineage plasticity following androgen receptor (AR) pathway inhibition. Although MYC family oncogenes are central to prostate cancer progression, the role of MYCL (L-MYC) in NEPC has remained unclear. Here, we show that MYCL is selectively and robustly upregulated in NEPC patient samples and cell line models, whereas MYC is downregulated and MYCN remains low, revealing a lineage-associated MYC family switch. MYCL expression strongly correlates with the neuroendocrine lineage regulators ASCL1 and INSM1 and inversely with adenocarcinoma-associated genes. Mechanistically, MYCL activation is not driven by genomic amplification but reflects a permissive epigenetic landscape. Functionally, MYCL overexpression suppresses AR signaling and induces neuroendocrine-like transcriptional reprogramming, whereas MYCL knockdown disrupts neuroendocrine lineage identity and restores adenocarcinoma-associated gene expression, including MYC. We further identify ASCL1 and INSM1 as upstream regulators of MYCL, establishing a conserved neuroendocrine transcriptional axis. Together, these findings define MYCL as a lineage-specific regulator that drives neuroendocrine identity and plasticity in advanced prostate cancer.

cancer biology↗

bioRxiv2025

Social isolation upregulates takeout expression in female Drosophila melanogaster to promote sucrose feeding

Drosophila melanogaster provides a model system to examine how environmental stress interacts with sex to induce changes in brain function and behavior. Previous research suggests that social isolation induces changes in gene expression that encode a starvation-like brain state and reduce sleep. However, the extent to which social isolation alters behaviors via sex-specific brain changes is unclear. Here, we use Drosophila melanogaster to explore sex differences in chronic social isolation-induced behavioral and transcriptomic changes. We focused on takeout (to), a gene encoding a putative juvenile hormone-binding protein, as a target that is upregulated solely in females following social isolation. Male and female adult flies were exposed to chronic social isolation, and multiple behavioral sex differences were identified through tests of activity, motivation, aggression, and sugar consumption. RNA-seq analysis also identified several candidate genes that were associated with sex differences in isolation-induced behavioral changes. Our findings suggest that social isolation is sufficiently stressful to reveal latent sex differences in behavior, despite having no impact on survival. To expression and sucrose consumption were upregulated exclusively in females following social isolation. Following to knockdown in to-expressing cells, sucrose consumption decreased in socially isolated females but increased in males. However, to knock down, to overexpression, and transformer knock down in neurons did not change sucrose-feeding behavior between control and isolated females. Overall, our results suggest that manipulating to expression influences sucrose-feeding in opposite directions between females and males following social isolation, and that isolation-induced to overexpression in non-neuronal cells in the brain or head may play a role in communicating information about females nutritional status to the brain. Additional roles for to in stress-related behaviors and behavioral sex differences should be explored, as well as whether to participates in signaling pathways that may be functionally conserved in human disorders. Author SummaryChronic stress contributes to detrimental health effects, but our understanding of how stress induces sex differences in brain gene expression and behavior is incomplete. Here, we use a combination of behavioral testing, RNA sequencing, and genetic manipulations in Drosophila melanogaster to explore how social isolation reveals latent sex differences in gene expression and stress-relevant behaviors. We found the most pronounced sex differences in behaviors related to feeding and motivation. RNA profiling revealed isolated female-specific upregulation of over 100 genes, with many of them relating to reproduction and energy metabolism. We manipulated expression of the candidate gene takeout (to) and found that downregulating to in all to-expressing cells decreases sucrose-feeding in isolated females but increases it in isolated males. Our results suggest that within a chronic stress context, sex-specific effectors in the head may regulate gene expression related to feeding and macronutrient choice to ensure that females prioritize survival over reproduction. Learning more about this system in flies could provide insight into functionally analogous pathways in humans that may be dysregulated in female-biased stress-related disorders.

neuroscience↗

bioRxiv2025

Precision at Every Scale: Efficiency in AI-Driven De Novo Antibody Design

The precise de novo design of antibodies remains a therapeutic challenge. The AI platform, GaluxDesign, was evaluated in a high-efficiency Precision-Scale Workflow by synthesizing and testing only 50 full-length IgG candidates per epitope across eight distinct epitopes from six therapeutic targets. This campaign yielded a 10.5% binder rate (estimated EC50 < 100 nM), identifying target-specific binders for seven of eight epitopes, with multiple candidates exhibiting sub-nanomolar to single-digit nanomolar dissociation constants (Kd). We further assessed the same workflow on nine shared benchmark targets selected for external comparison, where GaluxDesign identified target-specific binders for eight of nine targets, demonstrating strong target-level performance relative to previously reported de novo antibody design approaches. Together, these results establish a high-efficiency, precision-scale workflow for generating novel, high-affinity therapeutic antibodies.

bioengineering↗

bioRxiv2025

CDR Conformation Aware Antibody Sequence Design with ConformAb

Antibody lead optimization methods seek to enhance a lead candidates therapeutic properties through targeted sequence mutation. However, the mutations introduced during this process can inadvertently induce structural changes that disrupt binding, particularly by altering CDR loop conformations which destabilize CDR-target binding interactions. To address this, we present ConformAb, a guided discrete diffusion model for designing antibody sequences that explicitly conform to the CDR canonical conformation of the lead. With seed sequences as the starting point, we show that our method is capable of generating 3- 5x better binders that conform to the same CDR backbone structure in a one-shot design setup, and in some cases, binders with better affinity than seed repertoire picks without any target-specific data included in training. Across the targets tested, ConformAb demonstrated binding rates ranging from 15 -60% in wet lab experiments, a result obtained using fewer than 100 designs for each target. ConformAb offers a unique one-shot approach for antibody lead optimization in data-scarce scenarios where experimental/repertoire data cannot be leveraged for model training.

biophysics↗

bioRxiv2025

Property Enhancer - a data efficient multi-objective approach for functional antibody optimization

In-silico antibody lead optimization remains challenging due to scarce high-quality data, costly experimental validation, and the need to jointly optimize multiple developability properties. Discovery workflows often rely on high-throughput phage, ribosome or yeast display experiments, which yield large but noisy datasets; as leads emerge, strategies shift to low-throughput assays which are precise, yet unscalable. Deep-learning and language-model approaches are hindered by such limited, unreliable measurements. We introduce Property Enhancer (PropEn), a data-efficient framework for low-data, heterogeneous regimes that can simultaneously optimize multiple antibody properties. PropEn proposes a matching-based augmentation that expands the training data with sequence pairs differing by only a few mutations; within each pair the second sequence improves the target value, providing an implicit optimization signal. Extensive in silico and in vitro tests show 10-39x affinity gains across four targets and nine leads, and enable joint multi-property optimization, positioning PropEn as a scalable, general solution.

molecular biology↗

bioRxiv2025

Tumor Genotype Dictates Mitochondrial and Immune Vulnerabilities in Liver Cancer

Although oncogenic alterations influence tumor metabolism, how they impose distinct metabolic programs within a shared tissue context remains poorly defined. Here, we developed a rapid mitochondrial profiling platform to compare metabolites and proteins in genetic models of primary liver cancer (PLC). Analyses of six genetically distinct PLCs revealed that mitochondrial energy metabolism is largely dictated by oncogene identity. Kras-driven tumors required creatine metabolism to buffer energy demands during early tumorigenesis, whereas c-MYC-driven tumors relied on oxidative phosphorylation. Among c-MYC-driven PLCs, Pten-deficient tumors accumulated mitochondrial phosphoethanolamine, a precursor for phosphatidylethanolamine (PE) synthesis. Inhibition of PE synthesis selectively impaired the growth of Pten-deficient tumors and extended survival, in part through enhanced infiltration of CD8 T cells and sensitization to TNF-mediated cytotoxicity. Mechanistically, loss of PE elevated surface TNF receptor 2 (TNFR2), promoting TNF signaling and pro-inflammatory response. These findings uncover genotype-specific mitochondrial metabolic liabilities and establish PE synthesis as a tumor-intrinsic mechanism of immune evasion in PLC.

cancer biology↗

bioRxiv2025

GLM-Prior: a nucleotide transformer model reveals prior knowledge as the driver of GRN inference performance

Gene regulatory network (GRN) inference depends on high-quality prior knowledge, yet curated priors are often incomplete or unavailable across species and cell types. We present GLM-Prior, a genomic language model fine-tuned to predict transcription factor (TF)-target gene interactions from nucleotide sequence, and benchmark it as a sequence-derived strategy for constructing TF-gene prior matrices. We integrate GLM-Prior with PMF-GRN, a probabilistic matrix factorization model, to create a dual-stage pipeline that combines sequence-derived priors with single-cell gene expression data for prior-conditioned GRN inference. Across six human, mouse, and yeast cell-line contexts, GLM-Prior performance scales with positive label abundance and TF coverage in training data, and shows abovechance agreement with independent reference networks in well-annotated mammalian contexts. We evaluate single-species, species-transfer, and multi-species training paradigms, finding that GLM-Prior can construct informative priors across related mammalian species, while transfer to yeast remains near chance. Comparisons with accessibility-based priors across multiple GRN inference methods show that GLM-Prior achieves the highest prior performance in four of five mammalian cell lines. Under these benchmarks, prior quality largely constrains achievable GRN inference performance, with expression-based inference providing prior-dependent refinement. Together, these results position GLM-Prior as a benchmarked workflow for transferable, sequence-derived prior construction in systems where matched experimental assays are unavailable.

genomics↗

bioRxiv2025

Th9-endothelial cell crosstalk promotes inflammatory atherosclerotic cardiovascular disease

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death, and understanding its pathogenic drivers is critical for effective prevention and treatment. Inflammation has a critical role in ASCVD, and patients with inflammatory diseases are at increased risk. However, the key inflammatory mediator promoting ASCVD are incompletely understood, a major barrier when targeting inflammation to prevent ASCVD. Here, we found that interleukin-9 (IL-9) producing T helper cells (Th9) were significantly associated with ASCVD in patients with the autoimmune disease psoriasis. Th9 cells were poised to migrate to coronary vessels and were identified in atherosclerotic plaque. In vivo, murine inflammatory atherogenesis was prevented by IL-9 blockade and by IL-9 receptor (IL-9R) deletion in endothelial cells. In human arterial endothelial cells, IL-9R/STAT3 signaling promoted endothelial dysfunction, angiogenesis, and release of leukocyte chemoattractants. These findings suggest that in autoimmune diseases like psoriasis, Th9/IL-9 promote atherosclerosis by directly targeting endothelial cells, and that IL-9R/STAT3 signaling could be a promising therapeutic target for ASCVD. eTOC SummaryBaral et. al. investigate individuals who are at high risk for atherosclerosis due to underlying inflammatory disease and use mouse models of cardiovascular disease to uncover a role for interleukin-9-producing T helper 9 cells in the pathogenesis of inflammatory atherosclerosis.

immunology↗