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PubMed2026

Integrative Multi-Omics Analysis Identifies Thrombosis-Associated Molecular Features Linked to Germline Susceptibility and Immune Cell Communication in Gastric Cancer.

Emerging evidence indicates that coagulation-related molecular programs are associated with thrombosis, tumor progression, and molecular dysregulation in gastric cancer (GC). However, thrombosis-associated molecular features in GC and their potential links to inherited susceptibility remain insufficiently understood. Integrated analyses of transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were performed to identify thrombosis-associated genes and establish a machine learning-based prognostic signature. Genome-wide association study (GWAS), expression quantitative trait loci (eQTL), transcriptome-wide association study (TWAS), and Mendelian randomization (MR) analyses were conducted to investigate susceptibility-associated transcriptional programs in GC. Functional assays were used to evaluate candidate genes associated with malignant phenotypes. Single-cell RNA sequencing (scRNA-seq) and cell-cell communication analyses were further performed to characterize cell-type-specific expression patterns and potential intercellular interactions. A total of 22 differentially expressed thrombosis-associated genes were identified, and a prognostic signature comprising 14 genes was established. The signature stratified patients into high- and low-risk groups and showed prognostic performance in both the training and validation cohorts. Integrative GWAS, eQTL, and TWAS analyses identified susceptibility-associated transcriptional programs that were positively correlated with the thrombosis-associated risk score. Silencing ACTN2 and CRYAB significantly reduced GC cell migration and invasion. scRNA-seq analysis revealed relatively high CRYAB expression in neutrophils, and CellChat analysis suggested potential neutrophil-B cell interactions involving COLLAGEN-related signaling. This integrative multi-omics study identified a thrombosis-associated molecular signature linked to prognosis and germline susceptibility-associated transcriptional programs in GC. ACTN2 and CRYAB may represent candidate genes associated with GC cell migration and invasion, while single-cell analysis suggested potential immune-related communication features.

Humans↗
PubMed2026

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans↗
PubMed2026

Proteomic analysis of pancreatic endocrine cells by mechanistic single-cell isolation identifies membrane pathways.

To better understand diabetes and normoglycemia, pancreatic islet biology requires a precise molecular understanding of islet cell types at both the transcriptomic and proteomic levels. While transcriptomic analyses are well established, comprehensive proteomic characterization has been lacking, limiting our knowledge of islet molecular complexity. Here we introduce a nonenzymatic, mechanistic single-cell isolation technology using laser microdissection (LMD7), facilitating proteomic and transcriptomic analysis of physically isolated α-, β- and δ-cells from fresh-frozen, unfixed pancreatic tissue. This mechanistic approach avoids enzymatic digestion and chemical fixation, preserving the cells' native molecular state before processing. Given the limited existing proteomic data, we supplemented our findings with transcriptomic analysis generated using the same method and compared our results with data from enzymatically isolated cells, obtained by fluorescence-activated cell sorting and compiled by others. Our analysis revealed that enzymatic digestion alters gene expression patterns, particularly those of membrane-associated proteins, underscoring the impact of isolation techniques on biological outcomes. We identified cell-type-specific proteins typically underrepresented in pancreatic single-cell transcriptomic datasets. β-cells exhibited enrichment in vesicle trafficking proteins, α-cells displayed distinct calcium-dependent action potential machinery and δ-cells showed elevated expression of focal adhesion-related proteins. In addition, we report an inverse molecular relationship between β- and δ-cells, potentially driven by transcriptional regulators such as Mlxipl. By establishing robust molecular profiles directly from intact pancreatic tissue, this work provides a reference point for future pathological comparisons, offering a framework to investigate how diabetes and other endocrine disorders reshape islet cell biology.

Journal Article↗
PubMed2026

Livestock Multi-Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation.

Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This review traces the progression from single-omics accumulation to multi-dimensional integration, highlighting how large-scale genomic, epigenomic, and transcriptomic projects lay the foundation for functional dissection. We identify core impediments: extreme species diversity, marked data heterogeneity, limited sample sizes, and a pervasive reduction of multi-omics data to simplistic differential screens, resulting in low translational efficiency. We critically appraise four common pitfalls-overinterpreting correlation as causation, relegating proteomics to corroborating transcriptomics, incomplete microbiome-host integration lacking environmental context, and systematic neglect of metabolic fluxomics-and show how exposomics and fluxomics add necessary causal and dynamic dimensions. To address these, we propose a livestock-adapted three-tier analytical framework: (1) statistical association of cross-omics covariation patterns; (2) machine learning-driven feature mining and integrative modeling; and (3) causal interpretation encompassing Mendelian randomization, prior-knowledge-guided network inference, and physical causal evidence via fluxomics and metabolic control analysis. We further discuss how multimodal sequencing (single-cell, spatial, temporal) and generative AI can fundamentally mitigate heterogeneity and strengthen causal evidence. Finally, we outline future priorities in database standardization, livestock-specific benchmarking, and translational pipelines, charting a path from correlation-centric reporting to mechanistic causality and precision breeding.

Animals↗
PubMed2026

A single-cell atlas of multiple myeloma defines malignant archetypes and proliferative states.

Multiple myeloma (MM) is a plasma-cell malignancy with extensive genomic and transcriptional heterogeneity, limiting disease classification and precision therapy. Here we generated a clinically annotated, population-scale, single-cell atlas of MM from 341 individuals spanning the disease and treatment continuum. We identified five recurrent malignant transcriptional archetypes and an orthogonal proliferative program associated with genomic features, therapeutic resistance and clinical outcomes. Validation in the independent CoMMpass cohort demonstrated robustness, prognostic relevance and portability across platforms. We developed a single-cell, target-discovery pipeline prioritizing malignant enrichment, cell-type specificity and tissue restriction, identifying FCRL2 as a plasma-restricted or B cell-lineage-restricted surface target expressed by malignant plasma cells. FCRL2-targeted chimeric antigen receptor T cells demonstrated antigen-specific activity in vitro and survival benefit in vivo. Together, these data provide a clinically actionable blueprint for patient stratification and precision target nomination in plasma-cell malignancies.

Multiple Myeloma↗
PubMed2026

Identifying fate-determining transcription factors with single-cell omics.

Single-cell sequencing enables the systematic discovery of cell fate-determining transcription factors (TFs), or key TFs, that define cellular identity or drive cell state transitions. A wide range of computational methods have been developed for this goal, but they differ substantially in the input data and the biological questions they address. In this article, we systematically review computational approaches for key TF identification and organize them from three perspectives: whether they identify TFs defining cell state identity or driving state transitions, whether transitions are modeled as discrete or continuous processes, and whether TFs act individually or combinatorially. We summarize key features and application scenarios of relevant methods to guide tool selection and discuss emerging trends in this field toward programmable and active control of cell fate.

Transcription Factors↗
PubMed2026

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption underlying morphology-based prediction models that metastatic risk can be inferred from static histological features alone. Here, we revisit lymph-node metastasis prediction in colorectal cancer through clonal ecology, integrating computational pathology with evolutionary oncology. Drawing on the subclonal switchboard model proposed in 2012 and subsequent artificial intelligence (AI)-enabled approaches for tracking dominant and dormant subclones, we synthesize evidence that metastatic potential reflects clonal ancestry, evolutionary timing, spatial niche architecture, cellular plasticity, intercellular interactions, dormancy, and treatment-driven shifts in subclonal fitness. We define five complementary methodological pillars for operationalizing clonal ecology: single-cell transcriptomics for resolving rare subclones, evolutionary trajectories, and adaptive cell states; lineage tracing and phylogenetics for reconstructing clonal ancestry and divergence; spatial transcriptomics and genomics for mapping subclonal geography and tumor-stromal-immune interactions; longitudinal liquid biopsy surveillance for monitoring residual disease, clonal turnover, and emerging resistance; and AI-enabled multimodal integration for connecting histopathology, genomics, spatial biology, and longitudinal data into predictive ecological-state models. Multiple-instance learning and pathology foundation models provide scalable computational foundations for evolution-aware prediction. Translationally, dormant subclones represent actionable reservoirs of recurrence. A longitudinal clinical and experimental study of KMT2A-rearranged acute myeloid leukemia further supports central predictions of the subclonal switchboard framework by demonstrating treatment-associated shifts in subclonal dominance, persistence of cryptic adaptive programs, and ecological rewiring during resistance and relapse. We propose clonal ecology as a measurable dimension for extending morphology-driven prediction toward integrative models that anticipate evolutionary transitions, identify therapeutic windows, and proactively constrain adaptive tumor ecosystems before resistant or metastatic subclones achieve clinical dominance.

Humans↗
PubMed2026

Immature Neutrophil Programs Associate With Burn Mortality and Extend Across Critical Illnesses.

Severe burns provoke a systemic "genomic storm," yet cell states associated with divergent outcomes remain unclear. We profiled blood cells by single-cell RNA-Sequencing (73 014 cells) from adult patients with burn injuries within postburn day 17 (n = 4) and healthy donors (n = 5), integrated data with bulk signatures of burn size, inhalation injury, and mortality, and evaluated clinical associations in the American Burn Association National Burn Repository. Burn was associated with emergency hematopoiesis marked by expansion of hematopoietic stem/progenitor-like cells, immature neutrophils, and plasmablast/plasma cell states, alongside depletion of naïve CD4+/CD8+ T cells and dendritic cells. Larger burns (>20% TBSA) showed enrichment of humoral transcriptional programs, including plasmablast/plasma cell activation and suppression of cytotoxic CD8+ T-cell states. In multivariable models, inhalation injury was a stronger predictor of death (adjusted odds ratio [OR] 1.9) than burn size (adjusted OR 1.1) and shared greater overlap with the most perturbed single cells in non-survivors; 55% of co-perturbed cells were neutrophils, implicating granulocyte dysregulation as a common lethal axis. We identified a neutrophil-specific 5-gene panel (OLFM4, RETN, LCN2, ARG1, and BTNL3) that discriminated survivors vs non-survivors after burns (area under the curve [AUC] > 0.9) and generalized to trauma (n = 158; AUC 0.81) and intensive care unit COVID-19 (n = 103; AUC 0.75), providing information orthogonal to conventional biomarkers and severity scores. Cytomorphology corroborated transcriptomic immaturity, with ~2-fold higher band neutrophils and larger neutrophil size in a fatal case. Computational drug-reversal analysis highlighted galectin-1 inhibition as a candidate modulator of mortality-associated neutrophil programs. Together, our findings suggest that immature neutrophils represent a shared immune feature across severe burns and other forms of critical illness.

Humans↗
PubMed2026

Clinical, Histopathological, and Molecular Characterization of Pediatric MN1::ZNF341-Associated Cancer.

A lethal round-cell malignancy with an MN1::ZNF341 fusion has recently been reported in three infants. Here, we describe four further tumors, three in newborns (including monozygotic twins), and one in an adolescent. Detailed clinical, radiological, and histopathological data differentiate these tumors from their main mimics, neuroblastoma and round-cell sarcomas. Single-cell RNA sequencing confirms the tumor to be transcriptionally distinct from neuroblastoma, instead exhibiting steroidogenic differentiation. Whole genome and targeted DNA sequencing yield no further driver events. Our work reveals a broader clinicopathological phenotype than previously appreciated and corroborates suggestions that this tumor is a distinct and aggressive childhood cancer.

Humans↗
PubMed2026

Unraveling lung cancer complexity: Spatial omics in tumor microenvironment characterization and precision medicine.

Heterogeneous tumor microenvironment (TME) in lung cancer plays a crucial role in disease progression and resistance to therapy. Despite advances in single-cell and bulk omics profiling, these methods often overlook spatial context, which is vital for understanding cell-cell interactions and regional heterogeneity. In recent years, spatial omics technologies-including spatial genomics, transcriptomics, proteomics, and metabolomics-have revolutionized the ability to map molecular landscapes while maintaining tissue architecture. These advancements have become essential components of next-generation lung cancer management. By providing unprecedented resolution in characterizing the lung cancer TME, spatial omics could reveal prognostic and predictive biomarkers and identify new therapeutic vulnerabilities. This review will provide the first critical evaluation of spatial multi-omics approaches for lung cancer prognosis. It will also assess various integration strategies for multi-omics data to explore the clinical translational potential of these tools for therapy selection and patient stratification. Therefore, a deeper understanding of spatial omics technologies and their application in lung cancer can significantly improve precision diagnostics and therapeutic decision-making.

Lung cancer↗
PubMed2026

Identification of CD55 as a downstream factor of EP4 receptor signaling in colorectal cancer cells.

Prostaglandin E2 (PGE2) signaling through the E-type prostanoid 4 (EP4) receptor has been implicated in the pathophysiology of colorectal cancer (CRC). We herein identified decay-accelerating factor, also known as CD55, as a novel CRC-associated downstream factor of the EP4 receptor. The integration of transcriptomic profiling of PGE2-stimulated HCA-7 human colon cancer cells with analyses of cancer genomic databases predicted CD55 as a potential EP4 receptor-regulated target. Inhibitor-based experiments showed the induction of CD55 after a PGE2 stimulation required the EP4 receptor and Gi protein in HCA-7 cells, whereas protein kinase A signaling was dispensable. In combination with a toxicogenomic database analysis, p38 mitogen-activated protein kinase (MAPK) was identified as the predominant effector connecting the EP4 receptor to CD55 upregulation. A single-cell RNA-seq re-analysis of human CRC tissues revealed CD55 upregulation and p38 MAPK-related gene set enrichment in epithelial cells expressing the EP4 receptor, suggesting that this induction mechanism may operate in a subset of epithelial cells in clinical specimens. Collectively, these results delineate a PGE2/EP4 receptor/Gi protein/p38 MAPK signaling axis that induces CD55 expression in HCA-7 cells and epithelial tumor cells, provide new mechanistic clues for understanding the regulation of complement regulatory molecule CD55 expression by prostaglandin signaling.

Humans↗
PubMed2026

A single-nucleus transcriptome atlas of soybean anthers.

Anther development is crucial for plant sexual reproduction. However, a high-resolution, cell-type-specific transcriptomic atlas of this process is lacking for the legume crop soybean (Glycine max). Here, we construct a comprehensive transcriptional atlas of developing soybean anthers using single-nucleus RNA sequencing (snRNA-seq). We identify and characterize nine distinct cell types spanning both somatic and reproductive lineages. Our analysis reveals robust transcriptional continuity across anther developmental stages and dynamic reprogramming during key transitions. Notably, the shift from diploid meiocytes to haploid unicellular microspores is marked by the induction of previously inactive genes, despite an overall reduction in transcript abundance. Subsequently, within bicellular microspores, generative and vegetative cell lineages exhibit sharply divergent transcriptional programs: generative cells specialize in mRNA export and turnover, whereas vegetative cells up-regulate translational machinery. Evolutionary analysis further indicates that generative-cell-specific genes are subject to more relaxed purifying selection compared to those specific to vegetative cells. Functional validation using mutants generated by CRISPR/Cas9-mediated genome editing and EMS mutagenesis reveals the essential roles of OSD1A and PKSA in pollen development and fertility. This high-resolution atlas provides fundamental insights into the transcriptional regulation of soybean anther development and serves as a valuable resource for manipulating male fertility to advance hybrid breeding programs. The data are available at https://databases.genedenovo.com/pollen.

Glycine max↗
PubMed2026

Peripheral pain threshold, glycaemic status, and LAMP3 genetic variation: A community-based analysis.

Diabetic polyneuropathy is a common complication of diabetes, yet substantial inter-individual variation in peripheral pain perception suggests underlying genetic influences. This population-based study investigated clinical, metabolic, and genetic determinants of pain threshold using intraepidermal electrical stimulation in 906 participants from the Iwaki Health Promotion Project 2017. Genome-wide association analysis identified 12 loci showing suggestive associations, among which a missense variant in LAMP3 (rs482912) was prioritized as a biologically plausible candidate. Phenotype-stratified analyses showed that individuals carrying the CT or CC genotypes had lower PINT indices than those with the TT genotype, indicating reduced pain thresholds. Notably, the CC genotype retained an association with lower pain threshold using intraepidermal electrical stimulation under conditions of metabolic stress, including impaired glucose tolerance, elevated HbA1c, and obesity, whereas this association was attenuated in the presence of hypertension. Single-cell RNA sequencing analysis of human skin revealed that LAMP3-positive mature dendritic cells, enriched in immunoregulatory molecules, exhibited transcriptional enrichment of inflammatory, antigen-presenting, and nociception-related pathways, including NF-κB, JAK-STAT, cytokine signaling, and neuroimmune sensitization cascades. Autopsy-based skin analysis further demonstrated genotype-associated differences in dermal LAMP3-positive cell infiltration and CD8-positive T-cell abundance, while CD4-positive T-cell abundance and intraepidermal nerve fiber density remained unchanged across genotypes. Taken together, these findings suggest a potential association between LAMP3 variation and individual differences in peripheral pain threshold and provide biological context supporting a role for neuroimmune interactions in early sensory modulation under metabolic stress. Given the suggestive genetic evidence and indirect mechanistic data, these observations should be interpreted as exploratory and hypothesis-generating.

Humans↗
PubMed2026

Disentangling covariate effects on single-cell-resolved epigenomes with DeepDive.

Understanding the effects of individual biological factors from single-cell-resolved epigenomic data is hindered by multicollinearity, particularly in human cohorts. We introduce DeepDive, a deep-learning framework designed to systematically disentangle known and unknown sources of variation in single-nucleus ATAC-seq data. DeepDive accurately reconstructs chromatin accessibility, outperforms state-of-the-art methods with incomplete covariate information, and robustly recovers true biological signals from even highly entangled covariates, unlocking counterfactual, "what-if," analyses. Applying DeepDive to pancreatic islet cells, we perform counterfactual analyses to prioritize covariates associated with a type 2 diabetes-linked beta-cell subtype and nominate transcription regulators. DeepDive offers a powerful and unbiased tool for mechanistic discovery in complex human disease cohorts.

disentanglement↗
PubMed2026

Protocol to identify genes required for cardiomyocyte development using Perturb-Seq.

While Perturb-Seq combines CRISPR-based screening with single-cell RNA sequencing (scRNA-seq), large-scale experiments are costly and its application during development is complicated by differentiation heterogeneity. Here, we present a protocol to identify genes required for cardiomyocyte development using Perturb-Seq. We describe steps for sgRNA (single guide RNA) library cloning and infection, cardiomyocyte differentiation, cell hashing, super loading, and scRNA-seq. We then detail procedures for sequencing, mapping, and data analysis. For complete details on the use and execution of this protocol, please refer to Sivakumar et al.1.

CRISPR↗
PubMed2026

Decoding the landscape of cell-type-specific co-expressed transcription factors in soybean.

Soybean (Glycine max) is an essential source of protein and oil with high nutritional value for human and animal consumption. To enhance our understanding of soybean biology, it is essential to have accurate information regarding the expression of each of its protein-coding genes. Here, we present Tabula Glycine max, a soybean single-cell resolution transcriptome atlas. This atlas comprises single-nucleus RNA-sequencing data from ten different G. max organs and morphological structures constituting the entire soybean plant. These nuclei are grouped into 156 different clusters based on their transcriptomic profiles. The breadth of various organs, tissues and cell types represented in Tabula Glycine max reveals that the pattern of co-expressed transcription factor genes is sufficient to define most cell types based on their function and organ of origin. Defining cell-type-specific co-expressed transcription factor genes offers a new perspective to engineer cell-type-specific programmes and enhance the biology of unique soybean cell types. This cellular resolution and breadth make the Tabula Glycine max an exceptional resource for the plant and soybean communities.

Journal Article↗
PubMed2026

ARX mutation-associated interneuron defects provide insights into mechanisms underlying developmental epilepsies.

Cortical interneuron (cIN) dysfunction is associated with various neurodevelopmental and neurological disorders, including developmental epilepsies, autism spectrum disorders and intellectual disabilities. Mutations in ARX (aristaless-related homeobox) are linked to these conditions, with or without accompanying structural brain anomalies. We previously demonstrated that the loss of Arx in the mouse ganglionic eminence, the birthplace of cINs, is associated with seizures, whereas its loss in cortical excitatory neuron progenitor cells results in structural anomalies but no seizures. To elucidate the pathophysiological role of ARX in cINs and its relationship to seizure phenotype, Arx conditional mutant mouse lines were investigated using Gad2- and Nkx2.1-Cre drivers to target distinct populations in the cIN lineage. Our data demonstrate that ARX abrogation results in defects in cIN density and distribution, as well as perinatal lethality. In these mice, we observed defects in cell cycle exit, a biased loss of the marginal zone migration stream of cINs, shifts in cell fate from caudal ganglionic eminence to medial ganglionic eminence identity, and a reduced number of parvalbumin⁺ and somatostatin⁺ cINs, with parvalbumin⁺ cINs being more severely affected. Single-cell RNA sequencing combined with chromatin immunoprecipitation and sequencing revealed that ARX regulates key processes involved in cell cycle progression, cIN subtype differentiation and cIN migration. Investigation of one downregulated target gene, Lmo1, uncovered a potential mechanism by which ARX regulates the number and distribution of cINs in the cortex. Cortical slice cultures demonstrate that LMO1 inhibits cIN migration by repressing Cxcr4 expression, which encodes a key receptor involved in cortical guidance. These data indicate that ARX positively regulates cIN migration by derepressing LMO1's repressive role. Consistent with our mouse model, we observed a significant loss of parvalbumin+ and somatostatin+ cINs in the brain of a patient carrying a pathogenic variant of ARX, who was diagnosed with developmental epileptic encephalopathy. Together, our data provide novel insights into how ARX and its target genes regulate cIN development and migration and into the pathogenic mechanisms underlying a spectrum of neurodevelopmental disorders linked to loss of ARX.

Animals↗
PubMed2026

Impaired Glycolysis Leads to Defective Efferocytosis and Impaired Plaque Resolution in Tet2 Clonal Hematopoiesis.

BACKGROUND: Clonal hematopoiesis (CH) arising from mutations in hematopoietic genes has been identified as an important risk factor for atherosclerotic cardiovascular disease. Despite the established role of some CH mutations in promoting atherosclerosis progression, their role in clinically relevant LDL (low-density lipoprotein) lowering-induced plaque remodeling or regression has not been extensively studied. METHODS: To assess the effects of TET2 (tet methylcytosine dioxygenase 2) CH on plaque resolution, we prepared control or chimeric Tet2+/- CH mice with conditional deletion of Tet2 in hematopoietic stem cells during LDL lowering-induced plaque remodeling. After establishing atherosclerosis by Western diet feeding for 12 weeks in Ldlr-/- mice, Tet2 was deleted by tamoxifen injection, and hypercholesterolemia was either normalized to simulate clinical lipid management, or mice were continued on the Western diet. RESULTS: Unlike control mice, Tet2+/- CH mice failed to significantly reduce necrotic core area or increase fibrous cap thickness and showed impaired macrophage efferocytosis during LDL lowering. Single-cell RNA sequencing and gene set enrichment analysis of aortic cell populations revealed that Tet2 deficient monocyte/macrophage populations were defective in glycolysis, phagocytosis, and actin polymerization. Tet2-deficient bone marrow-derived macrophages and Tet2+/- induced pluripotent stem cell-derived human macrophages showed defective ability to sustain continuing rounds of efferocytosis. Bone marrow-derived macrophages displayed reduced apoptotic cell binding and internalization and impaired activity of Wiskott-Aldrich syndrome protein and SCAR (suppressor of cyclic AMP receptor) homolog complex mediated actin polymerization. We linked these defects to reduced anaerobic glycolysis and lactate levels and rescued them by lactate supplementation or by treatment with the HIF-1α (hypoxia-inducible factor 1α) activator molidustat. Molidustat treatment reversed the defects in necrotic core and fibrous cap formation during LDL lowering-induced plaque remodeling in Tet2+/- CH mice. Reduced plasma lactate levels were also shown in TET2 clonal hematopoiesis of indeterminate potential carriers in the UK Biobank. CONCLUSIONS: Our data identify impaired efferocytosis and glycolysis-lactate-actin polymerization pathways in advanced atherosclerosis as potential therapeutic targets to induce proresolving restructuring of the plaque immune cells and to promote beneficial atherosclerosis remodeling in subjects with TET2 CH.

LDL lowering↗