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Enregistrement 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 sur 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

Notice bibliographique

RevueJHEP Reports · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueLiver Disease Diagnosis and Treatment
Établissements canadiensUniversity of Calgary
Organismes subventionnairesFundação de Amparo à Pesquisa do Estado de Minas GeraisConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
Mots-clésImmune systemBiologyMedicinePathologyImmunology

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,250

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,019
Tête enseignante GPT0,268
Écart entre enseignants0,249 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations14
Publié2020
Routes d'admission1
Résumé présentoui

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