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Characterizing the impact of plasma protein levels on human brain structure and disorders leveraging integrative multi-omics analysis.

With recent advances in high-throughput proteomic technologies, population-scale plasma proteomics datasets, often linked to extensive genetic and phenotypic information, have become increasingly accessible. Yet the relationships between circulating protein levels, brain imaging phenotypes, and risk for neurological and psychiatric disorders remain largely unexplored. Proteome-wide association studies offer a promising approach for elucidating biological mechanisms that connect genetic variation to complex brain-related traits and diseases. In this study, we integrated protein quantitative trait loci (pQTLs) from the two largest plasma proteomic resources (the UK Biobank Pharma Proteomics Project [UKB-PPP] and Ferkingstad et al. [deCODE]) with genome-wide association studies of brain imaging-derived phenotypes in UK Biobank using Mendelian randomization and colocalization analyses. We identified 120 cis and 20 trans associations between plasma proteins and imaging phenotypes and validated these findings using brain tissue-derived proteomic and transcriptomic datasets. Multivariable Mendelian randomization revealed eleven plasma proteins (coding genes APOE, ARL3, MICB, NSF, RHOC, RSPO3, ENPP2, BTN2A1, EIF2AK3, MRVI1, and OPLAH) with significant direct effects on the risk of Alzheimer's disease, Parkinson's disease, multiple sclerosis, bipolar disorder, and schizophrenia. Single-cell expression and pathway enrichment analyses further revealed cell-type-specific effects and distinct biological processes underlying these protein-disease associations. Together, these findings demonstrate robust links between plasma protein variation and brain structure, delineate protein-disease pathways, and highlight the cellular and molecular mechanisms that contribute to neurobiological diversity and pathology.

Journal Article↗

Time-dependent effects of rapid-acting antidepressants in iPSC-derived neurons from treatment-resistant depression and healthy volunteers.

Rapid-acting antidepressants like ketamine and serotonergic psychedelics show promise for treatment-resistant depression (TRD), but the molecular mechanisms that contribute to their therapeutic effects remain unclear. Induced pluripotent stem cells (iPSCs) offer a platform to model human cortical neurons and investigate drug effects in a human-relevant system. Here, iPSCs from individuals with TRD and healthy volunteers (HVs) were differentiated into mature cortical-like neurons and treated for six and 24 h with agents being investigated as rapid-acting antidepressants, including (2 R,6 R)-hydroxynorketamine (HNK), psilocybin, lysergic acid diethylamide (LSD), and 2,5-Dimethoxy-4-iodoamphetamine (DOI). Bulk and single-cell RNA sequencing assessed global and cell-type-specific transcriptomic responses. Synaptic proteins were evaluated via Western blotting and immunocytochemistry. To validate translational relevance, transcriptomic results were compared to CSF proteomics from ketamine-treated HVs. Despite differing initial pharmacological targets, overall gene expression across all compounds was highly correlated at matched timepoints compared to vehicle control, suggesting shared downstream effects. Both glutamatergic and serotonergic drugs converged on pathways involving inflammation, mTORC1 signaling, and cellular growth. At the single-cell level, (2 R,6 R)-HNK showed distinct cell-type specific alterations: upregulation in excitatory neurons and concomitant downregulation of inhibitory neuron populations. Differentially expressed genes from (2 R,6 R)-HNK-treated neurons also overlapped with CSF proteomic signatures from ketamine-treated individuals, supporting the model's translational relevance. This study is the first to assess multiple putative rapid-acting antidepressants in parallel using an iPSC-derived neuron model. Both convergent and drug-specific changes in gene expression and pathway enrichment were observed across diverse compounds, supporting the use of human iPSC-derived neurons in antidepressant drug discovery. Clinical Trial Registry: www.clinical trials.gov, NCT02484456.

Journal Article↗

Deciphering novel targets in salivary gland pleomorphic adenoma by integrating plasma proteomics and parotid transcriptomics analyses.

BACKGROUND/PURPOSE: Pleomorphic adenoma (PA) is the most common salivary gland benign tumor, with its molecular drivers elusive due to a lack of experimental models. This study aimed to decipher novel targets in PA by systematically integrating plasma protein quantitative trait loci (pQTL)-based Mendelian randomization (MR) with multi-omics profiling of parotid gland tissues. MATERIALS AND METHODS: We performed two-sample MR using 5450 plasma pQTLs and genome-wide association study summary for benign or broader salivary gland diseases from FinnGen consortium. Bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) comparing PA to normal tissue were used for transcriptomic validation. Immunohistochemistry (IHC) was applied for protein-level validation in human PA, adenoid cystic carcinoma (ACC), and murine inflammatory lesions. RESULTS: MR identified 12 plasma proteins associated with benign salivary gland tumor risk. Transmembrane serine protease 6 (TMPRSS6) was the only protein significantly risk-increasing for both benign and broader salivary gland diseases. Strikingly, mitogen-activated protein kinase kinase 4 (MAP2K4) showed opposite MR effects between benign and all-lesion outcomes. Bulk RNA-seq showed limited concordance with MR findings, while scRNA-seq revealed a unique plastic epithelium and partially validated candidates at cellular resolution. Critically, IHC confirmed MAP2K4 protein overexpression specifically in human PA, but not in ACC or inflammatory lesions, while TMPRSS6 was downregulated in established pathologies despite its genetic risk association. CONCLUSION: By integrating plasma proteome-based causal inference with parotid tissue multi-omics, this study unveils MAP2K4 as a potential PA-specific driver. This integrative framework provides novel, context-specific targets for further functional investigation in salivary gland tumorigenesis.

Gene expression profiling↗

Hepatic metabolic adaptation to endurance exercise: temporal and sex differences by multiomics integration and validation.

BACKGROUND: Although endurance exercise benefits liver health, sex-specific adaptive trajectories remain unclear. This study mapped dynamic liver adaptation in males and females during prolonged training and identified underlying molecular programs. METHODS: Using publicly available time-resolved liver multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), we established a computational pipeline for differential analysis of transcriptomic, proteomic, phosphoproteomic, and metabolomic data with FDR correction, followed by FGSEA pathway enrichment. Kinase activities were inferred through ortholog mapping and PhosphoSitePlus. Cross-omics co-expression networks were constructed using WGCNA and topological overlap to link omics features with physiological phenotypes. For experimental validation, liver tissues were collected from endurance-trained Sprague-Dawley rats, and key nodes were confirmed by Western blotting, qRT-PCR, and immunofluorescence/immunohistochemical staining. Public scRNA-seq data were further integrated to map multi-omics signals to single-cell resolution and assess functional changes in specific cell types. RESULTS: The hepatic response to exercise stress was stage-specific, shifting from early transcriptional activation to later proteomic and metabolic remodeling. Multi-omics integration revealed distinct sex-associated adaptive trajectories: males were more strongly associated with energy metabolism, redox-related programs, and amino acid/organic acid catabolism, whereas females showed prominent membrane lipid remodeling, proteostasis -related programs, and mitochondrial/ribosomal translational features. Single-cell analysis showed that tissue remodeling occurred without major lineage turnover, instead involving altered communication among pre-existing cell communities. Validation of PPP1R3G identified a protein-dominant exercise-responsive marker, supporting the contribution of post-transcriptional or protein-level regulation. CONCLUSIONS: Hepatic adaptation to endurance stress follows a cross-omics evolutionary pattern with sex-specific reprogramming of energy supply and homeostatic maintenance. This time-resolved framework clarifies how exercise improves liver function and supports sex-oriented metabolic interventions and therapeutic target discovery.

Animals↗

Single-cell transcriptomics reveals heterogeneous stress responses and Mg2+-mediated survival mechanisms in Lactobacillus delbrueckii subsp. bulgaricus during freeze-drying and storage.

Maintaining the viability of lactic acid bacteria during dehydration and subsequent storage remains a significant challenge. Here, we employed single-cell RNA sequencing to reveal the heterogeneous stress responses of Lactobacillus delbrueckii subsp. bulgaricus, identifying seven distinct transcriptional clusters across the liquid culture, freeze-drying, and storage phases. The dominant clusters in the freeze-drying and storage were not completely consistent, showing significant functional differentiation. Genomic stability may be important for survival during freeze-drying and storage, while intracellular energy homeostasis appears important for viability during storage. The magnesium transporter mgtB was highly expressed in clusters tolerant to freeze-drying and storage, suggesting a critical role for Mg2+ homeostasis. Further experimental validation confirmed that Mg2+ treatment significantly bolstered stress resistance, increasing immediate post-freeze-drying survival by over 2-fold (up to 92.90%) and post-storage survival by over 5-fold (up to 5.98%). Proteomic data indicated that Mg2+ supplementation correlated with the maintenance of several biological functions potentially relevant to bacterial survival during freeze-drying and storage, including DNA repair, translation, and central carbon metabolism. These findings provide a map of microbial stress resistance through population heterogeneity and offer a potential strategy that may be adapted for enhancing the stability of other industrial lactic acid bacteria products.

Freeze Drying↗

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on characterizing oocytes and ovarian tissue composition, as well as understanding the molecular mechanisms that guide ovarian function throughout its lifecycle. High-throughput omics technologies have enabled the characterization of different molecular layers, leading to substantial advances in our understanding of their complex dynamics. However, not all molecular aspects are studied equally, and studies examining the same modalities often show inconsistencies, underscoring the need for data standardization and highlighting the potential for using transformative artificial intelligence and machine-learning (AI/ML) methods for ovary studies. OBJECTIVE AND RATIONALE: This study aims to evaluate how multi-omic studies have advanced our understanding of the ovarian lifecycle from fetal development to postmenopause. We systematically reviewed published studies that have investigated molecular/omic layers, including the genome, methylome, transcriptome, and proteome throughout ovarian development and aging. Our analysis identified key molecular and cellular patterns, highlighted inconsistencies across studies and addressed gaps in data analysis, interpretation, and reproducibility to guide future research. SEARCH METHODS: We conducted a systematic literature search of Medline (PubMed), Embase (Ovid), and Web of Science Core Collection (Clarivate) using a combination of controlled and free text terms for human ovary, oogenesis, folliculogenesis, ovary development and (epi)genome, transcriptome, proteome, and multi-omic mechanisms to find relevant articles published before August 2025. To focus the scope of the current review, studies of domesticated and farm animals, rodents and other model organisms, non-human primates, as well as those examining various human ovarian pathologies were excluded. OUTCOMES: The search identified 23 546 studies for screening, of which 637 full-text studies were assessed for eligibility. Subsequently, we extracted data from 121 studies. Most studies analyzed the transcriptome of oocytes, granulosa cells, and ovarian tissue from reproductive-age individuals (n = 91), with fewer studies examining samples from individuals of advanced reproductive age (n = 45) and fetal (n = 16) samples. Transcriptome analyses were most common (n = 103, 85%), followed by proteome (n = 19, 16%) and epigenome (n = 14, 12%) studies. We found substantial variation in how studies defined and reported participants' groups as well as in their sequencing technologies and data analysis methods, with a lack of standardized reporting of background clinical information, data analysis methods, and pipeline details. The key findings underscore the prevailing consensus on genes defining major ovarian cell types and their roles throughout the ovarian lifespan, from prenatal development to postmenopausal transformation. This review highlighted the underrepresentation of certain patient groups, particularly prepubertal and peri-/postmenopausal individuals, among researched populations, due to obvious clinical and ethical reasons. WIDER IMPLICATIONS: This scoping review offers a comprehensive overview and benchmark of the current state of high-throughput omics-based research on ovarian cellular composition and molecular dynamics. To address these shortcomings, we propose general recommendations for multi-omics ovary studies and emphasize the necessity for more thorough multi-omic data integration by effectively applying novel AI/ML approaches. They can potentially improve the quality of multi-omics analyses at both single-cell and tissue levels despite limited sample sizes and enable integration of molecular profiling data with clinical and radiology datasets, enabling a more comprehensive understanding of ovarian biology. Such advancements can enhance reproducibility of research findings and guide future research to deepen our understanding of ovarian biology and ultimately support the development of medical technologies for better preserving fertility and alleviating infertility. REGISTRATION NUMBER: A protocol was published a priori on the Open Science Framework (https://osf.io/z38gb/).

Female↗

PRDX1 facilitates USP7-dependent stabilization of SCD1 and promotes bladder cancer progression.

Bladder cancer is characterized by redox adaptation and metabolic plasticity, but the mechanisms linking these processes remain incompletely understood. Integrating bulk, single-cell, and spatial transcriptomic analyses, we identified PRDX1 as a malignant epithelial cell-associated factor linked to adverse outcome. Genetic gain- and loss-of-function studies showed that PRDX1 promoted proliferation, motility, and xenograft growth while limiting reactive oxygen species accumulation and mitochondrial apoptosis. Proteomic and biochemical analyses identified an association between PRDX1 and SCD1. PRDX1 prolonged the SCD1 protein half-life without detectably altering SCD1 transcript abundance and increased USP7-SCD1 co-precipitation. USP7 removed K48-linked polyubiquitin chains from SCD1 and prevented its proteasomal degradation, whereas catalytically inactive USP7 failed to deubiquitinate SCD1. Deletion of PRDX1 residues 157-199 weakened its association with SCD1 and reduced USP7-SCD1 co-precipitation. Depletion of SCD1 or USP7 suppressed PRDX1-dependent growth in vitro and in xenografts. These findings support a model in which PRDX1 facilitates USP7-dependent stabilization of SCD1 and promotes bladder cancer progression.

Bladder cancer↗

Inferring metabolic objectives and trade-offs in single cells during embryogenesis.

While proliferating cells optimize their metabolism to produce biomass, the metabolic objectives of cells that perform non-proliferative tasks are unclear. The opposing requirements for optimizing each objective result in a trade-off that forces single cells to prioritize their metabolic needs and optimally allocate limited resources. Here, we present single-cell optimization objective and trade-off inference (SCOOTI), which infers metabolic objectives and trade-offs in biological systems by integrating bulk and single-cell omics data, using metabolic modeling and machine learning. We validated SCOOTI by identifying essential genes from CRISPR-Cas9 screens in embryonic stem cells, and by inferring the metabolic objectives of quiescent cells, during different cell-cycle phases. Applying this to embryonic cell states, we observed a decrease in metabolic entropy upon development. We further uncovered a trade-off between glutathione and biosynthetic precursors in one-cell zygote, two-cell embryo, and blastocyst cells, potentially representing a trade-off between pluripotency and proliferation. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗

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↗

A distinct effector B cell population drives autoantibody production in SARS-CoV-2 infection.

Autoantibodies (autoAbs) are linked to mortality and Long COVID, yet their cellular origins remain unclear. We analyzed the INCOV cohort and identified 12 age- and sex-matched participants with varying autoAb abundance and integrated single-cell RNA-seq and ATAC-seq data from B cells, plasma proteomics, proteome-wide autoAb profiling, clinical data, and in vitro assays. AutoAb abundance inversely correlated with neutralizing IgG and declined as infection resolved, paralleling the contraction of atypical memory B cells (AtMs). In vitro, AtMs preferentially differentiated into autoAb-producing antibody-secreting cells upon TLR7/8 stimulation. CD11c+ AtMs (double-negative 2, DN2s) in autoAb-high individuals exhibited increased TLR7 signaling, oxidative stress, and isotype switching, regulated by transcription factors T-bet and XBP1. Integrated genetic and genomic analyses showed that DN2s had the strongest enrichment for autoimmune trait heritability and inferred regulatory effects of autoimmune risk variants among B cell subsets. These findings identify DN2s as key precursors of autoAb-producing cells during SARS-CoV-2 infection.

B cell↗

Pre-treatment polyfunctionality percentage (PFA) of CD8+ T cells is associated with development of immune-related adverse events (irAEs) in patients receiving immune checkpoint inhibitors (ICIs).

INTRODUCTION: Immune checkpoint inhibitors (ICIs) have improved cancer survival, but immune-related adverse events (irAEs) occur frequently and can have devastating consequences. There are no validated methods to evaluate risk of irAEs prior to initiation of ICIs. MATERIALS AND METHODS: We conducted a pilot study evaluating the ability of blood-based, single-cell secretomic analysis to characterize irAEs. A total of 10 patients with thoracic malignancies who were scheduled to receive ICIs were enrolled. Each patient had a pre-ICI blood sample drawn as well as a sample at the time of irAE development or 12 weeks after ICI initiation, whichever came first. Utilizing IsoPlexis's IsoLight system, polyfunctionality percentages (PFAs) and strength indices (PSIs) were analyzed for CD4+ and CD8+ T cells. RESULTS: Five patients developed irAEs and 5 patients did not develop irAEs. Pre- and post-ICI CD8+ T cell PFA was significantly elevated in patients who developed irAEs compared with those who did not (p = 0.017 and p = 0.014, respectively). CONCLUSIONS: In this pilot study, pre-ICI CD8+ T cell PFA was associated with development of irAEs. While this is a pilot study, this is a first step toward developing a blood-based, streamlined assay to assess risk of irAEs prior to initiation of ICIs. Validation in larger cohorts is warranted.

Humans↗

Acbd7 is essential for preserving hair cell-mediated auditory and vestibular function.

Understanding the molecular basis of hair cell function is essential for elucidating inner ear physiology and developing therapies for auditory-vestibular disorders. Here, we identify acyl-CoA binding domain-containing 7 (Acbd7) as a hair cell-specific gene critical for sensory maintenance. Single-cell transcriptomics of mouse cochlear organoids revealed Acbd7 as a top hair cell-enriched transcript, with its spatiotemporal expression confirmed from embryonic development through adulthood in both auditory and vestibular hair cells. Acbd7‑deficient mice exhibited pronounced hair cell degeneration, characterized by synaptic defects and diminished calcium currents in inner hair cells and loss of outer hair cells. Transcriptomic and proteomic analyses linked Acbd7 to the regulation of Ca2+ signaling and fatty acid metabolism pathways. Our findings establish Acbd7 as a critical regulator of Ca2+ homeostasis and functional integrity in hair cells, thereby elucidating a key mechanism by which a fatty acid metabolism factor sustains hair cell function and providing potential therapeutic targets for inner ear disorders.

Animals↗

A pro-inflammatory metastasis-associated macrophage subset induces tumor-promoting mesothelial cell conversion in ovarian cancer via IL-1α secretion.

Tumor-associated macrophages (TAMs) are key regulators of the tumor microenvironment, yet the functional specialization of TAM subsets in metastatic progression remains incompletely defined. Here, we characterized distinct TAM populations contributing to tumor-promoting mesothelial cell conversion in high-grade ovarian carcinoma using single-cell RNA sequencing of patient-derived macrophages from ascites (ascTAMs) and omental metastases (omTAMs). TAMs from these anatomical sites were clearly distinguishable by polarization states, with omTAMs exhibiting a mixed M1⁺/M2⁺ phenotype, in contrast to the M1low/M2⁺ profile observed in ascTAMs. Transcriptomic analysis further revealed functional divergence of these subsets. Notably, omTAMs displayed gene signatures associated with mesothelial-to-mesenchymal transition (MMT), a critical process enabling tumor invasion across the peritoneal lining. Functionally, conditioned media from omTAMs, similar to that from classically activated M1 macrophages, induced MMT in primary mesothelial cells via TGFβ and ERK/p38 MAPK signaling pathways. This phenotypic transition enhanced transmesothelial tumor cell invasion. Proteomic analysis identified IL-1α as a key MMT-inducing factor secreted by pro-inflammatory macrophages. Mechanistically, IL-1α cooperates with TGFβ by activating an autocrine TGFβ/TGFBR1 feedback loop in mesothelial cells, thereby amplifying MMT. Consistent with these findings, IL1A expression was enriched in omTAM clusters across independent patient samples and was confirmed by immunohistochemical analysis of clinical samples. From a therapeutic perspective, our study identifies new avenues to counteract the mesothelial reprogramming driven by IL-1α⁺ TAMs, potentially impeding metastatic progression. Created in BioRender. Heidemann, S. (2026) https://BioRender.com/aeu6yd0 .

Female↗

RNA splicing and cardiovascular disease: a guide for cardiologists.

Alternative splicing (AS) is a fundamental RNA processing mechanism, which generates different RNA transcripts and consequently different protein isoforms from a single gene. This increases the diversity of proteins within an organism and can fine-tune biological processes. This review examines how cardiac-enriched RNA-binding proteins establish heart-specific splicing programs governing aspects of cardiac development, function, and disease. Developmentally, coordinated sarcomeric isoform switches underpin the foetal-to-adult transition and further isoform rewiring in ion channel and kinase genes determine electrophysiology and excitation-contraction coupling. AS contributes to the pathogenesis of several cardiomyopathies and emerging datasets suggest that pathological hypertrophy engages distinct splicing signatures compared with physiological hypertrophy. This review summarizes diagnostic and prognostic opportunities arising from bulk, long-read, and single-cell/nucleus transcriptomics, which resolve cell type-specific isoforms and disease-associated switches. Circulating RNA biomarkers (including splice ratios and circularRNAs) may signify myocardial remodelling and arrhythmic risk. Integrative approaches that link AS with proteomics and genomics improve variant interpretation, reveal previously unannotated protein isoforms, and enable tracking of disease progression and therapy response. Finally, an outline of therapeutic strategies to modulate AS in cardiovascular disease (CVD), including antisense oligonucleotides, small molecules, and genome-editing modalities (CRISPR, base, and prime editing), is provided. The major challenges that remain before splice-targeting therapeutics can be targeted to treat cardiovascular disease are highlighted. Lessons from neuromuscular indications establish clinical feasibility of splicing correction and motivate translation to cardiology. Together, mechanistic insight, biomarker development, and therapeutic innovation position RNA splicing as a tractable axis for precision cardiovascular medicine.

Humans↗

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.

Journal Article↗

Integrative Analysis Uncover the Effects and Multi-Omics Features of Thigh Muscle Fat Infiltration.

The health impacts and underlying biological pathways of thigh muscle fat infiltration (TMFI) remain incompletely understood. In this study, we analyzed TMFI measured by magnetic resonance imaging in 55,120 UK Biobank participants and found that higher TMFI was significantly associated with all-cause mortality as well as with all major system-specific diseases examined (p values ranged from 2.50&#x2009;&#xd7;&#x2009;10-88 to 9.97&#x2009;&#xd7;&#x2009;10-04). TMFI also mediated the effects of lifestyle factors on health-related outcomes, with mediation proportions ranging from 6.7% to 71.7%. A genome-wide association study (GWAS) identified 79 lead single nucleotide polymorphisms (SNPs) linked to TMFI, and the polygenic risk score for TMFI was significantly associated with mortality and all incident diseases across examined organ systems in an independent subset of UK Biobank participants of European ancestry who were not included in the TMFI GWAS (n&#x2009;=&#x2009;362,286, all p&#x2009;<&#x2009;0.05). Gene-drug interactions identified multiple drugs that could potentially modulate TMFI. Analysis of single-cell transcriptomic data indicated that myogenic cells were strongly linked to TMFI (p&#x2009;=&#x2009;7.08&#x2009;&#xd7;&#x2009;10-08). Summary-data-based Mendelian randomization and Transcriptome-Wide Association Study analyses revealed numerous genes whose expression in specific tissues was associated with TMFI. Proteomic and metabolomic profiling uncovered a broad array of circulating biomarkers associated with TMFI, many of which mediated the effects of modifiable factors and genetic risk on TMFI. Overall, our results highlight the biological relevance of TMFI to human health and provide insights into the multi-omics mechanisms underlying TMFI, identifying potential targets for interventions.

Humans↗

Spatiotemporal mapping of tertiary lymphoid structure heterogeneity shapes immune niches and clinical outcomes in intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy with limited therapeutic options. The spatial architecture and functional diversity of tertiary lymphoid structures (TLSs) in iCCA remain unclear. Here, we present a multimodal spatial atlas of TLSs and identified intratumoral TLSs (iTLSs) as independent prognostic markers. Bulk proteomic profiling of 214 discovery and 155 validation cases identified a four-tier TLS-based tumor microenvironment classification system and supported development of a TLS-predictive random forest classifier. Imaging mass cytometry revealed that iTLS+ tumors harbor structured immune architectures, where M1-like tissue-resident macrophages (RTMs), dendritic cells, and CXCL13+ CD4+ T cells colocalize to form antigen-presenting neighborhoods (apc-CNs) spatially coupled to TLS core regions (TLScore-CNs). Single-cell spatial transcriptomics further resolved 61 TLSs into 14 spatial niches and defined a pseudotemporal maturation continuum: aggregated, activated, and postactivated. Intraniche communication, primarily mediated by ifnCAFs, iCAFs, and CXCL12+ macrophages, evolved dynamically with maturation. Single-nucleus RNA sequencing combined with Tangram-based spatial mapping revealed CXCL12+ macrophages and iCAFs forming a peripheral band in aggregated TLSs, whereas ifnCAFs infiltrated TLS interiors during activation. These findings define TLS heterogeneity and provide insights for stroma-directed immunotherapy.

Cholangiocarcinoma↗

HIF1A+CSF3R+ neutrophils-dominated hypoxic niche induced metabolic reprogramming for neoadjuvant therapy resistance in NSCLC.

BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the frequently occurring cancers characterized by molecular heterogeneity and multiple immune cell infiltration patterns, which are associated with treatment sensitivity and resistance. However, the specific microenvironmental cells and their mechanisms that lead to treatment resistance in patients need to be explored in greater depth. METHODS: On the basis of patients receiving neoadjuvant therapy in our center, a multicenter, multicohort NSCLC spatial transcriptome, single-cell transcriptome, T-cell receptor repertoire sequencing, bulk RNA transcriptome, phosphorylated proteome, genome mutation, and clinical data were included for a comprehensive assessment of the therapeutic and prognostic impact of HIF1A+ CSF3R+ neutrophils in NSCLC. In vitro experiments validated the functional phenotype of HIF1A+ CSF3R+ neutrophils and co-localization interactions with other cellular subpopulations. Gradient boosting machine (GBM) constructed region of interest (ROI) models for evaluation. Computer-aided drug design (CADD) was used to predict targeted small molecule drugs, and in vivo mouse models were constructed to assess the effectiveness of the combination treatment regimen. RESULTS: Centered on HIF1A+ CSF3R+ neutrophils, recruited exhausted T cells and stromal cells form a hypoxic niche within the tumor region, which was enriched in non-response patients. ROI composed of these specific cellular subpopulations, associated with senescence and glycolysis, accurately predicting NSCLC progression, prognosis, and microenvironment composition. CADD analysis identified that platycodin-D2 specifically targeted CSF3R, reducing HIF1A expression and inhibiting neutrophil activity. Combining navitoclax, platycodin-D2 with anti-programmed cell death protein 1 (PD-1) significantly suppressed tumor proliferation and improved the immunosuppressive microenvironment. CONCLUSION: Our study emphasized the role of HIF1A+ CSF3R+ neutrophils in immunotherapeutic resistance of NSCLC, constructed a microenvironmental immune dysregulation network in a hypoxic ecological niche with HIF1A+ CSF3R+ neutrophils as the center. Platycodin-D2 specifically targeted HIF1A+ CSF3R+ neutrophils, enhancing the efficacy of anti-PD-1 therapy in NSCLC.

Humans↗