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We are analyzing https://www.biorxiv.org/content/10.1101/2025.04.16.649149v2.

Title:
A Single-Cell Atlas Of Human Pediatric Liver Reveals Age-Related Hepatic Gene Signatures | bioRxiv
Description:
Background & Aims The liver plays a critical role in metabolism and immune function, yet the contributions of its heterogeneous cell types to these processes remain unclear. While most liver studies focus on adults, pediatric liver diseases often present differently, underscoring the need for age-specific research. Approach & Results To better understand cellular drivers of childhood liver diseases, we generated single-cell RNA-seq (scRNA-seq) maps of the normal pediatric liver and used this map to examine disease-related populations in biopsies from pediatric patients with Intestinal Failure-Associated Liver Disease (IFALD). The normal pediatric liver map consists of 42,660 cells from 9 donors aged 2-17 years. Compared to normal adult liver (26,372 cells; 7 donors, age 26-69) pediatric livers exhibited differences in myeloid populations. Specifically, pediatric Kupffer-like cells ( MARCO + C1QA + VSIG4 +) exhibited higher expression of immune activation genes, including CCL4, CCL3 and IL1B. In vitro stimulation confirmed more IL1-β secreting myeloid cells in pediatric versus adult livers, supporting these findings. Using the pediatric atlas as a reference, we analyzed three IFALD biopsies (11,969 cells; 3 donors, ages 4 months–9 years) and identified increased expression of fibrosis-associated genes (e.g., LY96 ) in Kupffer-like cells. Additionally, mesenchymal cells in IFALD showed fibrotic gene modules resembling adult liver cells more than healthy pediatric cells. These signatures, undetectable when comparing IFALD to adult liver alone, highlighting the value of a pediatric map. Conclusions Taken together, our healthy pediatric liver atlas reveals distinct age-related signatures and provides background against which to interpret pediatric liver disease data. ![Figure][1]</img> ### Competing Interest Statement The authors have declared no competing interest. * AI : Artificial Intelligence ALT : Alanine Transaminase cDC1 : Conventional Type 1 Dendritic Cells DC : Dendritic Cells DAPI : 4’,6-diamidino-2-phenylindole FDR : False Discovery Rate FFPE : Formalin-Fixed Paraffin-Embedded FMO : Fluorescence Minus One FGSEA : Fast Gene Set Enrichment Analysis GO : Gene Ontology GRCh38 : Genome Reference Consortium Human Build 38 H&E : Hematoxylin and Eosin HCA : Human Cell Atlas HSC : Hepatic Stellate Cells IFALD : Intestinal Failure-Associated Liver Disease KC-like cells : Kupffer Cell-like cells LPS : Lipopolysaccharide MAFLD : Metabolic Dysfunction-Associated Fatty Liver Disease MASH : Metabolic Dysfunction-Associated Steatohepatitis Mono-Mac : Monocyte-like Macrophages NPC : Non-parenchymal Cells PBMC : Peripheral Blood Mononuclear Cells PC : Principal Component PCA : Principal Component Analysis PN : Parenteral Nutrition PSC : Primary Sclerosing Cholangitis REB : Research Ethics Board rPCA : Robust Principal Component Analysis scRNA-seq : Single-cell RNA sequencing TLH : Total Liver Homogenate Canadian Institutes of Health Research, , NHC&#8208;142832, HIT168002 Canadian Network on Hepatitis C, , Public Health Agency of Canada, https://ror.org/023xf2a37, Chan Zuckerberg Initiative (United States), , CZF2019-002429, CZF2021-23792, CZF2022-316558 University of Toronto’s Medicine by Design, , Canada First Research Excellence Fund, , Toronto General and Western Hospital Foundation, , UHN Foundation, , [1]: pending:yes
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12 years and 2 months (reg. 2013-04-08).