Single-cell atlas of human pediatric liver reveals age-related hepatic gene signatures
Bibliographic record
Abstract
BACKGROUND: 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. METHODS: To better understand cellular drivers of childhood liver diseases, we generated single-cell RNA-sequencing 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). RESULTS: The normal pediatric liver map consists of 42,660 cells from 9 donors under 17 years of age. Compared with 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 IL-1β-secreting myeloid cells in pediatric versus adult livers, supporting these findings. Using the pediatric atlas as a reference, we analyzed 3 IFALD biopsies (11,969 cells; 3 donors, under 9 y of age) and identified increased expression of fibrosis-associated genes (eg, LY96) in Kupffer-like cells. In addition, 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, highlight the value of a pediatric map. CONCLUSION: Taken together, our healthy pediatric liver atlas reveals distinct age-related signatures and provides a background against which to interpret pediatric liver disease data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".