Imaging and immunometabolic phenotyping uncover changes in the hepatic immune response in the early phases of NAFLD
Bibliographic record
Abstract
BACKGROUND & AIMS: The precise determination of non-alcoholic fatty liver disease (NAFLD) onset is challenging. Thus, the initial hepatic responses to fat accumulation, which may be fundamental to our understanding of NAFLD evolution and clinical outcomes, are largely unknown. Herein, we chronologically mapped the immunologic and metabolic changes in the liver during the early stages of fatty liver disease in mice and compared this with human NAFLD samples. METHODS: Liver biopsies from patients with NAFLD (NAFLD activity score [NAS] 2-3) were collected for gene expression profiling. Mice received a high-fat diet for short periods to mimic initial steatosis and the hepatic immune response was investigated using a combination of confocal intravital imaging, gene expression, cell isolation, flow cytometry and bone marrow transplantation assays. RESULTS: We observed major immunologic changes in patients with NAS 2-3 and in mice in the initial stages of NAFLD. In mice, these changes significantly increased mortality rates upon drug-induced liver injury, as well as predisposing mice to bacterial infections. Moreover, deletion of Toll-like receptor 4 in liver cells dampened tolerogenesis, particularly in Kupffer cells, in the initial stages of dietary insult. CONCLUSION: The hepatic immune system acts as a sentinel for early and minor changes in hepatic lipid content, mounting a biphasic response upon dietary insult. Priming of liver immune cells by gut-derived Toll-like receptor 4 ligands plays an important role in liver tolerance in initial phases, but continuous exposure to insults may lead to damage and reduced ability to control infections. LAY SUMMARY: Fatty liver is a very common form of hepatic disease, leading to millions of cases of cirrhosis every year. Patients are often asymptomatic until becoming very sick. Therefore, it is important that we expand our knowledge of the early stages of disease pathogenesis, to enable early diagnosis. Herein, we show that even in the early stages of fatty liver disease, there are significant alterations in genes involved in the inflammatory response, suggesting that the hepatic immune system is disturbed even following minor and undetectable changes in liver fat content. This could have implications for the diagnosis and clinical management of fatty liver disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".