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At least 19 recordsLinked to original sources

PubMed2026

QCatch: a framework for quality control assessment and analysis of single-cell sequencing data.

MOTIVATION: Single-cell sequencing data analysis requires robust quality control (QC) to mitigate technical artifacts and ensure reliable downstream results. While tools like alevin-fry and simpleaf (and augmented execution context for the alevin-fry), offer flexibility and computational efficiency to process single-cell data, this ecosystem will further benefit from a standardized QC reporting tailored for its outputs. RESULTS: We introduce QCatch, a Python-based command-line tool that generates comprehensive and interactive HTML QC reports designed specifically for single-cell quantification results. Taking the output directory of alevin-fry or simpleaf as the input, QCatch is able to perform essential processing steps, like cell calling, and generate detailed QC reports that contain informative visualizations and statistics, including unique molecular identifier (UMI) count distributions, sequencing saturation estimates, and splicing status information, for QC assurance. Built for seamless integration into downstream analysis workflows, QCatch exports the processed results in a richly-annotated H5AD format file, a widely used data format common among many downstream single-cell data analysis tools. AVAILABILITY AND IMPLEMENTATION: The source code and documentation of QCatch are available on GitHub at https://github.com/COMBINE-lab/QCatch. QCatch can be installed via both Bioconda and PyPI.

Single-Cell Analysis↗

PubMed2025

Stereo-cell: Spatial enhanced-resolution single-cell sequencing with high-density DNA nanoball-patterned arrays.

Single-cell sequencing technologies have advanced our understanding of cellular heterogeneity and biological complexity. However, existing methods face limitations in throughput, capture uniformity, cell size flexibility, and technical extensibility. We present Stereo-cell, a spatial enhanced-resolution single-cell sequencing platform based on high-density DNA nanoball (DNB)-patterned arrays, which enables scalable and unbiased cell capture at a wide input range and supports high-fidelity transcriptome profiling. Stereo-cell further allows integration with imaging-based modalities and multiomics strategies, including immunofluorescence and epitope profiling. This platform is also compatible with profiling extracellular vesicles, microstructures, and large cells, whereas its spatial resolution facilitates in situ analysis of cell-cell interactions, cellular microenvironments, and subcellular transcript localization. Together, Stereo-cell provides a flexible framework for expanding single-cell research applications.

Animals↗

PubMed2026

The role of KIAA1467 in breast cancer: insights from pan-cancer and single-cell sequencing analysis.

BACKGROUND: Improving the response rate of single-agent immune checkpoint blockade (ICB) urgently requires the discovery of new therapeutic targets for combinatorial regimens. Analyses of tumor microenvironment (TME)-associated biomarkers have verified that KIAA1467 drives the formation of an immune-excluded, non-inflamed TME in breast cancer (BRCA). This study systematically explores the expression pattern, prognostic value, immune regulatory function, biological effects, and drug resistance relevance of FAM234B (also known as KIAA1467) in BRCA. METHODS: We performed pan-cancer survival analysis using The Cancer Genome Atlas (TCGA) datasets. Multi-omics bioinformatics analyses were conducted to evaluate KIAA1467 expression across malignancies. Single-cell RNA sequencing (scRNA-seq) data from GSE176078 was utilized to localize KIAA1467 expression at the cellular level. Immunohistochemistry and western blot assays validated KIAA1467 expression in BRCA clinical specimens. Correlation analyses were implemented to assess relationships between KIAA1467 expression, clinicopathological features, immune modulators, tumor-infiltrating immune cells, and p53 mutation status. Functional enrichment analysis uncovered relevant signaling pathways. Bioinformatic half maximal inhibitory concentration (IC50) prediction and in vitro cellular experiments were applied to evaluate associations between KIAA1467 and chemotherapeutic drug sensitivity. RESULTS: TCGA pan-cancer survival analysis demonstrated that elevated KIAA1467 expression significantly predicted shortened overall survival in BRCA and multiple other tumor types. KIAA1467 displayed distinct expression patterns across cancers, with prominent upregulation in BRCA. scRNA-seq confirmed enriched KIAA1467 expression within BRCA cells, and its upregulation in BRCA tissues was further verified by immunohistochemistry and western blot. High KIAA1467 expression was positively correlated with advanced tumor grade and lymphatic metastasis. KIAA1467 showed negative correlations with most immune modulators and core immune checkpoint molecules, as well as tumor-infiltrating immune cells in the TME, implying its potential function in tumor immune evasion. Low KIAA1467 expression was tightly linked to p53 mutations. Enrichment analysis indicated participation of KIAA1467 in epithelial-mesenchymal transition, apoptosis and cell cycle arrest. Furthermore, high KIAA1467 expression corresponded to higher estimated IC50 values of cisplatin, gefitinib, paclitaxel and gemcitabine, consistent with reduced chemosensitivity observed in vitro. CONCLUSIONS: This study reveals the multifaceted oncogenic role of KIAA1467 in BRCA. KIAA1467 participates in remodeling an immunosuppressive TME, correlates with malignant progression and chemoresistance, and may serve as a promising candidate target to optimize ICB-based combination therapy for BRCA. These findings offer new perspectives for the clinical treatment and comprehensive management of BRCA.

KIAA1467↗

PubMed2024

An isoform-resolution transcriptomic atlas of colorectal cancer from long-read single-cell sequencing.

Colorectal cancer (CRC) ranks as the second leading cause of cancer deaths globally. In recent years, short-read single-cell RNA sequencing (scRNA-seq) has been instrumental in deciphering tumor heterogeneities. However, these studies only enable gene-level quantification but neglect alterations in transcript structures arising from alternative end processing or splicing. In this study, we integrated short- and long-read scRNA-seq of CRC samples to build an isoform-resolution CRC transcriptomic atlas. We identified 394 dysregulated transcript structures in tumor epithelial cells, including 299 resulting from various combinations of splicing events. Second, we characterized genes and isoforms associated with epithelial lineages and subpopulations exhibiting distinct prognoses. Among 31,935 isoforms with novel junctions, 330 were supported by The Cancer Genome Atlas RNA-seq and mass spectrometry data. Finally, we built an algorithm that integrated novel peptides derived from open reading frames of recurrent tumor-specific transcripts with mass spectrometry data and identified recurring neoepitopes that may aid the development of cancer vaccines.

Colorectal Neoplasms↗

PubMed2026

Single-cell sequencing reveals synovial fluid γδ T-cell expansion in equine experimental osteoarthritis.

OBJECTIVE: Define temporal cellular changes following joint injury using single-cell RNA sequencing in experimental equine posttraumatic osteoarthritis (PTOA). METHODS: PTOA was induced in 4 Quarter Horses (3 to 5 years) via carpal osteochondral fragmentation and high-speed treadmill exercise. Synovial fluid (SF) cells and synovium were sampled over 18 weeks (November 2023 to April 2024). Single-cell suspensions were processed (10x Genomics Chromium iX), then aligned to the equine genome (Cell Ranger). Downstream analysis was completed in the R Seurat package. Differential gene expression (log2[fold change] > 1; P < .05) and differential abundance analyses were performed (P < .1). RESULTS: Cartilage injury had a modest impact on gene expression changes and cell abundance shifts in SF. Integrated analysis of 90,323 SF cells across 4 time points revealed 9 distinct cell types, primarily T cells (73 ± 19%) followed by myeloid cells (20 ± 13%). Subcluster analysis of T cells revealed 9 transcriptomically distinct subtypes (3 CD8, 2 CD4, 3 γδ, and 1 cycling). Differential abundance analyses of temporal changes identified increased γδ T and decreased CD4+ T-cell subsets in joints over time. Expanded populations of IL-23 receptor-positive γδ T cells exhibited increased T-helper 17 signatures. CONCLUSIONS: IL-23 receptor-positive γδ T-cell expansion, associated with joint inflammation, occurred in PTOA. Limitations include small sample size and individual heterogeneity; further investigation over extended timeframe is necessary to confirm whether later stages of the experimental model reflect natural chronic OA. CLINICAL RELEVANCE: Cellular immunotherapy targeting γδ T cells and IL-23/IL-17 blockade may warrant investigation to mitigate equine OA progression.

equine↗

PubMed2025

Growth Hormone Alleviates Atherosclerosis Through Regulating the Activity of PI3K/AKT Pathway: Insights From Single-Cell Sequence and Mechanism Exploration.

PURPOSE: This research sought to investigate the impact and underlying mechanisms of growth hormone (GH) on atherosclerosis (AS) based on the analysis of single-cell RNA sequencing (scRNA-seq) data. METHODS: We analyzed the impact of GH on arterial vascular smooth muscle cells (VSMCs) by utilizing scRNA-seq data obtained from both atherosclerotic and healthy vascular tissues in mice. AS was induced in C57BL/6 and ApoE-/- mice through hypophysectomy performed via the parapharyngeal approach, followed by a high-fat diet (HFD), resulting in the C57-Hx and ApoE-/--Hx models. AS was evaluated by measuring arterial lipid deposition, plaque progression, collagen loss, vascular inflammation, and oxidative stress. Serum metabolite alterations were assessed using liquid chromatography-mass spectrometry (LC-MS). RNA sequencing was employed to examine the underlying mechanisms of GH in the context of AS treatment, with findings further confirmed through western blot analysis. In vitro experiments involved treating VSMCs with oxidized low-density lipoprotein (ox-LDL) to simulate atherosclerotic injury. The formation of foam cells was evaluated by measuring lipid accumulation, inflammatory responses, apoptosis, and the expression levels of foam cell-related markers. Finally, the PI3K/AKT inhibitor LY294002 confirmed that GH alleviates AS via the PI3K/AKT signaling pathway. RESULTS: scRNA-seq data analysis showed that growth hormone signaling was reduced in VSMCs of atherosclerotic arteries. HFD led to elevated levels of serum total cholesterol (TC), triglycerides (TGs), and low-density lipoprotein cholesterol (LDL-C), accompanied by increased lipid deposition, inflammatory responses, and oxidative stress. In contrast, high-density lipoprotein cholesterol (HDL-C) and insulin-like growth factor 1 (IGF-1) levels were lower in C57-Hx mice. GH treatment improved HFD-induced AS in ApoE-/--Hx mice. LC-MS analysis revealed that GH altered lipid metabolism in serum samples from C57-sham, C57-Hx, ApoE-/--Hx, and ApoE-/--Hx-GH(3) mice. GH maintained lipid balance by increasing 1-palmitoyl-2-oleoyl-sn-glycerol-3-phosphocholine (POPC), PE-NMe2(18:1(9z)/18:1(9z)) (DMPE), and 4-chloro-2-nitrobenzylalcohol levels and decreasing 1-heptadecanoyl-sn-glycerol-3-phosphocholine. RNA sequencing showed significant gene expression differences in the aortas of C57-sham and C57-Hx mice. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that GH inhibited the progression of AS by modulating the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling pathway, a finding that was validated through western blotting. Further in vitro studies demonstrated that GH exerted protective effects on VSMCs against ox-LDL-induced damage through activation of the PI3K/AKT pathway, as evidenced by experiments using the specific PI3K inhibitor LY294002. CONCLUSION: GH alleviates the development of AS through the activation of the PI3K/AKT pathway. The findings of this research emphasize the therapeutic potential of GH in inhibiting AS and highlight the importance of the PI3K/AKT pathway as a promising target for clinical intervention.

PI3K/AKT signaling pathway↗

PubMed2026

FZD5 drives macrophage-mediated immunomodulation and predicts prognosis in glioma: evidence from single-cell sequencing.

BACKGROUND: Gliomas are highly malignant brain tumors characterized by an immunosuppressive microenvironment, which limits therapeutic efficacy and contributes to poor clinical outcomes. The WNT/β-catenin signaling pathway is critically involved in tumor progression, and FZD5, a key receptor within this pathway, may participate in immune regulation. However, its specific role and underlying mechanisms in glioma remain unclear. METHODS: RNA-seq and microarray datasets from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA), together with single-cell RNA sequencing (scRNA-seq) datasets from GEO, were comprehensively analyzed. The Seurat package was used to identify macrophage-related clusters and mitophagy-associated pathways. Cox and LASSO regression analyses, along with a prognostic nomogram, were applied to evaluate the prognostic significance of FZD5. Immune infiltration, functional enrichment, and immunotherapy response analyses were conducted, followed by validation using spatial transcriptomics, immunohistochemistry, and in vitro assays. RESULTS: In bulk glioma transcriptomes, FZD5 emerged as an independent predictor of poor prognosis. Crucially, single-cell and spatial analyses revealed that the biologically significant FZD5 signal originated predominantly within tumor-associated macrophages (TAMs), where it colocalized with the M2 marker CD163. Consistently, elevated FZD5 levels correlated with increased myeloid infiltration and an immunosuppressive tumor microenvironment. Functionally, macrophage-expressed FZD5 was associated with mitophagy-related programs and promoted an M2-skewed phenotype, thereby enhancing glioma cell proliferation, migration, and invasion via macrophage-glioma crosstalk. CONCLUSION: FZD5 is a TAM-enriched marker in glioma tissues and a potential regulator of macrophage-associated immunosuppressive programs, supporting its utility as a prognostic biomarker and a candidate target for microenvironment-oriented interventions in glioma.

Humans↗

PubMed2024

Single-cell sequencing shows mosaic aneuploidy in most human embryos.

Mammalian preimplantation embryos often contain chromosomal defects that arose in the first divisions after fertilization and affect a subpopulation of cells - an event known as mosaic aneuploidy. In this issue of the JCI, Chavli et al. report single-cell genomic sequencing data for rigorous evaluation of the incidence and degree of mosaic aneuploidy in healthy human in vitro fertilization (IVF) embryos. Remarkably, mosaic aneuploidy occurred in at least 80% of human blastocyst-stage embryos, with often less than 20% of cells showing defects. These findings confirm that mosaic aneuploidy is prevalent in human embryos, indicating that the process is a widespread event that rarely has clinical consequences. There are major implications for preimplantation genetic testing of aneuploidy (PGT-A), a test commonly used to screen and select IVF embryos for transfer. The application and benefit of this technology is controversial, and the findings provide more cause for caution on its use.

Pregnancy↗

PubMed2026

Integrative analysis of single-cell sequencing identifies CD8+ TIM3+ CD101+ T cell-associated genes as prognostic biomarkers in breast cancer.

BACKGROUND: Breast cancer is a prevalent and deadly malignancy that significantly impacts women's quality of life and imposes financial burdens. Despite therapeutic advancements, tumour heterogeneity and frequent relapses remain major challenges. Accordingly, this study aimed to characterize immune features associated with CD8+ TIM3+ CD101+ T cells and develop a prognostic signature for breast cancer. METHODS: This study integrated single-cell and bulk transcriptomic datasets to characterize CD8+ TIM3+ CD101+ T cell (CCT)-related immune features and construct a prognostic signature in breast cancer. Single-cell RNA-seq data were sourced from the Gene Expression Omnibus (GEO) repository, and bulk transcriptomic data were from The Cancer Genome Atlas (TCGA) and GEO databases. Analytical methods included pseudo-time trajectory reconstruction (Monocle2), intercellular signalling analysis (CellChat), functional enrichment (ClusterProfiler), and immune profiling (ssGSEA). Prognostic modeling was conducted using least absolute shrinkage and selection operator (LASSO) Cox regression, with validation via Kaplan-Meier and time-dependent receiver operating characteristic (ROC) analyses. RESULTS: Single-cell analysis identified 17 clusters spanning seven cell types, including T cells, myeloid cells, and epithelial cells. T-cell sub-clustering revealed four subtypes. Pseudotime analysis suggested a potential state-transition relationship between CD8+ CD101- TIM3+ and CD8+ CD101+ TIM3+ T-cell states. A total of 121 differentially expressed genes were enriched in vital biological processes. An 11-gene prognostic model showed strong predictive power across cohorts. Single-cell T-cell reclustering identified a CD8+ CD101+ TIM3+ T-cell subpopulation, which was primarily characterized by the expression of markers such as CD101 and HAVCR2/TIM3. CONCLUSIONS: This study maps cellular heterogeneity and molecular networks in breast cancer, offering insights for targeted therapy and improved prognosis.

Breast invasive carcinoma↗

PubMed2026

Proteomics combined with single-cell sequencing reveals key genes and computational lead compound related to ligamentum flavum hypertrophy, lactate metabolism and lactate modification.

Ligamentum flavum hypertrophy (LFH) is a hallmark pathological feature of lumbar spinal stenosis; however, its underlying molecular mechanisms remain incompletely understood. Lactate metabolism and related lactylation modifications have emerged as critical links between cellular metabolism and epigenetic regulation, with established roles in various fibrotic and inflammatory diseases. Nevertheless, the specific contribution of lactylation to LFH pathogenesis remains unexplored. In this study, we integrated proteomic profiling of ligamentum flavum tissues with single-cell transcriptomic data to identify differentially expressed proteins associated with LFH. Cross-referencing these genes with genes involved in lactate metabolism and lactylation yielded 16 candidate genes. Through functional enrichment analysis, protein-protein interaction network construction, and GraphBAN model prediction, we identified five hub genes (NDUFS2, HMOX1, SPR, FABP5, and PFKP) and two potential lead compounds (ZINC000014879975 and ZINC000242437513). Molecular docking analysis confirmed favorable binding affinities between these compounds, suggesting that they may serve as potential lead compounds worthy of further experimental investigation. Single-cell analysis further revealed that macrophages occupy a central position in the LFH microenvironment, resulting in pronounced metabolic reprogramming and remodeling of intercellular communication networks, particularly via the MIF-CD74/CD44 axis, under pathological conditions.

Proteomics↗

PubMed2023

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis.

Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably high accuracy. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement, shedding light on genetic changes affecting specific cell types across development. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities and unveil genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. When cell types are obscured by stress signals, label transfer from primary tissue improves the accuracy of cortical organoid annotations, serving as a reliable ground truth. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Brain organoids↗

PubMed2025

simPIC:flexible simulation of paired-insertion counts for single-cell ATAC sequencing data.

Single-cell Assay for Transposase Accessible Chromatin (scATAC-seq) is increasingly used at population scale to study how genetic variation shapes chromatin accessibility across diverse cell types. This widespread adoption of the assay has created a need for computational methods that can handle complex biological and technical variation. Yet method development is limited by the lack of flexible simulation tools with known ground truth. Here, we present simPIC, a simulation framework for generating realistic single-cell ATAC-seq data across individuals and cell types. simPIC supports both population-scale and single-individual simulations, with the ability to model cell groups, batch effects, and genotype-dependent variation in accessibility. These features enable realistic benchmarking for tasks such as chromatin accessibility quantitative trait locus (caQTL) mapping. simPIC generates data that closely match real datasets and better captures inter-individual and experimental variation compared to existing tools.

simulation↗

PubMed2025

Absolute copy number aware CNV calling of sub-megabase segments in ultra-low coverage single-cell DNA sequencing data.

Recent advances in ultra-low coverage whole-genome sequencing (WGS) of single cells have enabled detailed analysis of copy number variation at a throughput approaching that of single-cell RNA sequencing. However, downstream computational methods have not seen comparable advances and are largely adaptations of deep sequencing methodology with reduced precision. Here, we present ASCENT, a computational method built to take full advantage of modern direct tagmentation-based WGS at ultra-low depth. Using joint segmentation with high-resolution bins, we accurately detect small segments, achieving accurate copy number profiles even at 100 000 reads per cell. ASCENT implements true absolute copy state inference for single cells, based on statistical modeling of coverage rather than comparison to a reference, while taking variable segment copy state into account. Further, ASCENT implements per-segment copy-neutral loss of heterozygosity (LOH) calling without the need for non-tumor or bulk WGS reference. When applied to a pediatric B-ALL sample, ASCENT finds copy-neutral LOH in a small segment and a minor subclone defined by breakpoints missed in bulk WGS. Thus, by applying appropriate computational methods, single-cell WGS provides clear advantages over bulk, even at a relatively low cell number and sequencing depth.

DNA Copy Number Variations↗

PubMed2024

Heat Inactivation of Nipah Virus for Downstream Single-Cell RNA Sequencing Does Not Interfere with Sample Quality.

Single-cell RNA sequencing (scRNA-seq) technologies are instrumental to improving our understanding of virus-host interactions in cell culture infection studies and complex biological systems because they allow separating the transcriptional signatures of infected versus non-infected bystander cells. A drawback of using biosafety level (BSL) 4 pathogens is that protocols are typically developed without consideration of virus inactivation during the procedure. To ensure complete inactivation of virus-containing samples for downstream analyses, an adaptation of the workflow is needed. Focusing on a commercially available microfluidic partitioning scRNA-seq platform to prepare samples for scRNA-seq, we tested various chemical and physical components of the platform for their ability to inactivate Nipah virus (NiV), a BSL-4 pathogen that belongs to the group of nonsegmented negative-sense RNA viruses. The only step of the standard protocol that led to NiV inactivation was a 5 min incubation at 85 °C. To comply with the more stringent biosafety requirements for BSL-4-derived samples, we included an additional heat step after cDNA synthesis. This step alone was sufficient to inactivate NiV-containing samples, adding to the necessary inactivation redundancy. Importantly, the additional heat step did not affect sample quality or downstream scRNA-seq results.

Nipah Virus↗

PubMed2025

Effect of acupuncture on brain microenvironment in rats with post-stroke limb spasticity based on single-cell transcriptome sequencing technology.

OBJECTIVE: To investigate the possible mechanisms by which acupuncture improves post-stroke limb spasticity using single-cell sequencing technology. METHODS: Thirty-two rats were randomly assigned to four groups: Control, Sham, Model, and Acupuncture. The middle cerebral artery occlusion (MCAO) model was established, and the acupuncture groups received acupuncture treatment. After treatment, brain morphological changes and the degree of neurological impairment were assessed. The effect of acupuncture on the proportion of brain cell types in the ischemic penumbra of MCAO rats was analyzed using single-cell transcriptomics, and the expression and enrichment of differentially expressed genes were examined. Finally, selected differential genes were validated by Western blot and quantitative real-time polymerase chain reaction. RESULTS: Triphenyltetrazolium chloride staining showed that the infarct area in MCAO rats was significantly reduced after acupuncture. Garcia scoring, hematoxylin-eosin staining, Nissl staining, and terminal deoxynucleotidyl transferase dUTP nick end labeling demonstrated that acupuncture reduced brain damage. Enzyme-linked immunosorbent assay results showed that acupuncture significantly decreased serum inflammatory factors, including interleukin-1 beta (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Single-cell transcriptome analysis revealed marked changes in cell type proportions between the Acupuncture and Model groups. A total of 207 differential genes were identified, including 157 upregulated and 50 downregulated genes. Analysis of macrophage-specific differential genes in the ischemic penumbra showed enrichment in Gene Ontology terms such as Ras protein signal transduction and regulation of GTPase activity, and Kyoto Encyclopedia of Genes and Genomes pathways including lysosome, axon guidance, and mitogen-activated protein kinase signaling. S100a8 and leukocyte specific transcript 1 (LST1) were identified as key differential genes. CONCLUSION: These findings suggest that the key differential genes S100a8 and LST1 may alleviate post-stroke limb spasticity by regulating the inflammatory response in the ischemic penumbra.

Animals↗

PubMed2026

Inflammatory cytokines mediate thoracic aortic aneurysm formation via plasma metabolites: A two-step Mendelian randomization and single cell sequencing-based investigation.

Thoracic aortic aneurysm (TAA) is a life-threatening condition characterized by pathological dilation of the aorta. While inflammatory responses have been implicated in TAA pathogenesis, the causal relationships remain elusive. This study aimed to elucidate potential causal associations between inflammatory cytokines, plasma metabolites, and TAA risk using Mendelian randomization (MR) analysis. We conducted bidirectional two-sample MR analysis utilizing genome-wide association study data from 91 inflammatory cytokines (n = 14,824), 1400 plasma metabolites (n = 8299), and TAA (n = 385,857). The inverse-variance weighted method served as the primary analytical approach, with comprehensive sensitivity analyses performed to assess pleiotropy and heterogeneity. Two-step MR analysis was employed to explore potential mediating roles of plasma metabolites. Single-cell sequencing analysis was utilized to detect cell type enrichment and elucidate cellular functions of identified cytokines. Additionally, we conducted an analysis to identify druggable proteins as potential therapeutic targets for TAA. MR analysis revealed that genetically-determined increases in C-X-C motif chemokine 10 (CXCL10) (odds ratios [OR] = 1.149, 95% confidence interval [CI]: 1.009-1.309, P = .037) and fibroblast growth factor 5 (OR = 1.101, 95% CI: 1.013-1.196, P = .024) were associated with elevated TAA risk. Conversely, C-C motif chemokine 20 (CCL20) (OR = 0.870, 95% CI: 0.759-0.996, P = .043) and CD40L receptor (CD40) (OR = 0.906, 95% CI: 0.827-0.992, P = .033) demonstrated inverse associations with TAA risk. Two-step MR analysis identified potential mediating metabolites: the phosphate to linoleoyl-arachidonoyl-glycerol ratio for CXCL10, thyroxine and X-24585 for FGF-5, and the creatine to carnitine ratio for CCL20. Single-cell sequencing analysis revealed enrichment of these cytokines in specific cell types and pathways relevant to TAA pathogenesis. Drug-gene interaction analysis identified CXCL10, CCL20, and CD40 as potential targets for treatment of TAA. This study provides robust genetic evidence supporting causal relationships between specific inflammatory cytokines and TAA risk, with plasma metabolites potentially mediating these effects. CXCL10 and FGF-5 were identified as potential risk factors, while CCL20 and CD40 may confer protective effects. These findings offer novel insights into TAA pathogenesis and suggest potential targets for intervention. Further research is warranted to elucidate the underlying mechanisms and validate these results across diverse populations.

Aortic Aneurysm, Thoracic↗

PubMed2026

Single-cell RNA sequencing reveals disease associated changes in brain endothelial cells in the 5XFAD mouse.

Vascular dysfunction is a key contributor to Alzheimer’s disease (AD) pathology, where changes to the endothelium and its crucial role in maintaining blood-brain barrier (BBB) integrity have been of particular emphasis. The transgenic 5XFAD (5X Familial Alzheimer’s Disease) mouse model, which exhibits AD-related amyloidosis through FAD associated mutations in amyloid precursor protein (APP) and presenilin-1 (PS1), has become a widely adopted preclinical model in AD-related research studies. The need for cross-study standardization, accessibility, and data reproducibility has led to the widespread implementation of the C57BL/6J genetic background for maintaining this model. However, its reliability for studying vascular dysfunction and BBB alterations has been questioned due to conflicting reports in the literature. This variation is often attributed to the previously documented protective nature of the C57BL/6J background and loss of genetic background diversity. Since prior studies have mostly relied on imaging or functional assays, we herein utilized single-cell RNA sequencing (scRNAseq) to investigate AD-related molecular changes to endothelial cell populations in the 5XFAD mouse model. To initially build this resource, we focused on 12-month-old male mice, which revealed differentially expressed genes between 5XFAD and wildtype animals that mapped to signaling pathways involved in DNA damage, immune reactivity, and inflammation, among others. Many of these transcriptomic changes were zonated along the arteriovenous axis and occurred in AD genome-wide association study (GWAS) risk-associated genes. Overall, we anticipate this resource will help clarify the use of the 5XFAD model for studying AD-associated vascular changes and provide the foundation for expanded molecular profiling of brain endothelial cells under AD-associated conditions.

Animals↗

PubMed2026

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans↗