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Record W3018166881 · doi:10.1016/j.jhepr.2020.100117

Imaging and immunometabolic phenotyping uncover changes in the hepatic immune response in the early phases of NAFLD

2020· article· en· W3018166881 on OpenAlexaff
Ariane Barros Diniz, Maísa Mota Antunes, Viviane Aparecida de Souza Lacerda, Brenda Naemi Nakagaki, Maria Alice Freitas Lopes, Hortência Maciel de Castro Oliveira, Matheus Silvério Mattos, Kassiana Mafra, Camila Dutra Moreira de Miranda, Karen Marques de Oliveira Costa, Mateus Eustáquio Lopes, Débora Moreira Alvarenga, Raquel Carvalho-Gontijo, Sarah Cozzer Marchesi, Débora Romualdo Lacerda, Alan de Araujo, Érika de Carvalho, Bruna Araújo David, Mônica Morais Santos, Cristiano Xavier Lima, Juliana de Assis Silva Gomes, Tereza Cristina Minto Fontes Cal, Cláudia Alves Couto, Luciana Costa Faria, Paula Vieira Teixeira Vidigal, Adaliene Versiani Matos Ferreira, Sridhar Radhakrishnnan, Matthew Ricci, A. G. de Oliveira, Rafael M. Rezende, Gustavo Batista Menezes

Bibliographic record

VenueJHEP Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity of Calgary
FundersFundação de Amparo à Pesquisa do Estado de Minas GeraisConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsImmune systemBiologyMedicinePathologyImmunology

Abstract

fetched live from OpenAlex

•Hepatic immune response is already altered in liver biopsies from patients with mild NAFLD.•We designed a novel mouse model to mimic mild NAFLD, enabling the chronological mapping of liver changes.•This revealed an increased mortality rate upon secondary liver damage and a window of increased susceptibility to infection.•NAFLD diagnosis may be significantly improved by a more profound investigation of changes in hepatic immunology.•These data could guide customized nutritional and therapeutic interventions at different stages of NAFLD. Background & AimsThe 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.MethodsLiver 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.ResultsWe 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.ConclusionThe 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 summaryFatty 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. 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. 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. 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. 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.250

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.268
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations14
Published2020
Admission routes1
Has abstractyes

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