Deciphering cellular heterogeneity and pathway dynamics in urinary samples: a UMAP-Based approach to understanding acute kidney injury.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40900831", "kind": "science-record", "revision": 4, "content_hash": "sha256:5f14c02d93a6bcf5f8d3f3f959062d888d2a23eed935feebd3f7c5c40f078029", "created_at": "2026-11-01T20:31:00Z", "updated_at": "2026-11-01T22:57:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Deciphering cellular heterogeneity and pathway dynamics in urinary samples: a UMAP-Based approach to understanding acute kidney injury.", "doi": "10.3389/fphar.2025.1573469", "pmid": "40900831", "authors": ["Cheng Yuan", "Juan Wu", "Yuandi Xiang", "Lihua Ni"], "journal": "Frontiers in pharmacology", "year": 2025, "abstract": "Background: Acute kidney injury (AKI) is characterized by rapid loss of renal function and is associated with severe clinical outcomes. Understanding the cellular heterogeneity in urine samples during AKI may provide insights into the underlying pathophysiological mechanisms and potential therapeutic targets.\nObjectives: To explore the cellular composition and gene expression patterns in urine samples from AKI and non-AKI conditions using Uniform Manifold Approximation and Projection (UMAP) to identify key cellular interactions and pathway activations related to AKI.\nMethods: We utilized publicly available the dataset GSE180595 from the Gene Expression Omnibus (GEO) database. Urine samples were collected from AKI and non-AKI patients. Single-cell RNA sequencing (scRNA-seq) was performed to profile the mononuclear cell populations. Differential gene expression analysis was conducted to identify key molecular pathways, with a focus on ECM-related pathways. MAPK1 expression was quantified and compared between the two patient groups.\nResults: UMAP analysis revealed significant differences in cellular composition between AKI and non-AKI samples. Fifteen unique cell clusters were identified, each associated with distinct transcriptional profiles. In AKI samples, increased clustering of immune response cells such as monocytes was observed. Pathway analysis highlighted enhanced activation of DNA replication and ECM-related genes pathways in cells from AKI conditions, indicating their potential roles in injury response and tissue remodeling. The differential gene enrichment analysis identified ECM-related pathways as significantly enriched in the AKI group, with MAPK1 being a crucial gene regulating these pathways.\nConclusion: Our findings provide evidence that MAPK1 is upregulated in urinary mononuclear cells of AKI patients and plays a key role in regulating ECM-related pathways. MAPK1 could serve as a potential biomarker for AKI diagnosis and prognosis and may represent a promising therapeutic target for limiting ECM remodeling and fibrosis in AKI. Further studies are needed to explore the clinical implications of targeting MAPK1 in AKI treatment.", "claims": [{"id": "claim-method", "statement": "Differential expression was determined using DESeq2, with a significance threshold of adjusted p-value (FDR) < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40900831", "locator": "sections[16] \"Statistical analysis\" paragraph 2", "quote": "Differential expression was determined using DESeq2, with a significance threshold of adjusted p-value (FDR) < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. 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The names of the repository/repositories and accession number(s) can be found in the article/supplementary material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our findings provide evidence that MAPK1 is upregulated in urinary mononuclear cells of AKI patients and plays a key role in regulating ECM-related pathways.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40900831", "locator": "sections[0] \"Abstract\" paragraph 5", "quote": "Our findings provide evidence that MAPK1 is upregulated in urinary mononuclear cells of AKI patients and plays a key role in regulating ECM-related pathways."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Our findings provide evidence that MAPK1 is upregulated in urinary mononuclear cells of AKI patients and plays a key role in regulating ECM-related pathways.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40900831"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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Single-cell RNA sequencing (scRNA-seq) was performed to profile the mon", "on-AKI patients. Single-cell RNA sequencing (scRNA-seq) was performed to profile the mononuclear ce", "tudy is presented in Figure 1. Comprehensive single-cell RNA sequencing was employed to elucidate the diversity in R", "guishing the cell identities (Figures 2A,B). Single-cell RNA sequencing analysis of urine from AKI and non-AKI patie"], "order_basis": "paper_text_order:836", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["d from AKI and non-AKI patients. Single-cell RNA sequencing (scRNA-seq) was performed to profile the mon", "ented in Figure 1. Comprehensive single-cell RNA sequencing was employed to elucidate the diversity in R", "cell identities (Figures 2A,B). Single-cell RNA sequencing analysis of urine from AKI and non-AKI patie", "chart illustrates the process of single-cell RNA sequencing (scRNA-seq) analysis of urine samples from p"], "order_basis": "paper_text_order:848", "id": "assay:2"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Differential expression was determined using DESeq2, with a significance threshold of adjusted p-value (FDR) < 0.05."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}