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Enregistrement W1989601885 · doi:10.1074/jbc.m112.350181

Peroxisome Proliferator-activated Receptor γ Activation by Ligands and Dephosphorylation Induces Proprotein Convertase Subtilisin Kexin Type 9 and Low Density Lipoprotein Receptor Expression

2012· article· en· W1989601885 sur OpenAlexaff
Yajun Duan, Yuanli Chen, Wenquan Hu, Xiaoju Li, Xiaoxiao Yang, Xin Zhou, Zhinan Yin, Deling Kong, Zhi Yao, David P. Hajjar, Lin Liu, Qiang Liu, Jihong Han

Notice bibliographique

RevueJournal of Biological Chemistry · 2012
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiquePeroxisome Proliferator-Activated Receptors
Établissements canadiensUniversity of Saskatchewan
Organismes subventionnairesTianjin Science and Technology CommitteeNational Natural Science Foundation of ChinaNational Science Foundation
Mots-clésPCSK9LDL receptorProprotein convertasePeroxisome proliferator-activated receptorKexinChemistryBiologyDephosphorylationEndocrinologyReceptorInternal medicineCell biologyLipoproteinCholesterolPhosphorylationBiochemistryMedicinePhosphatase

Résumé

récupéré en direct d'OpenAlex

Proprotein convertase subtilisin kexin type 9 (PCSK9) plays an important role in cholesterol homeostasis by enhancing the degradation of LDL receptor (LDLR) protein. Peroxisome proliferator-activated receptor γ (PPARγ) has been shown to be atheroprotective. PPARγ can be activated by ligands and/or dephosphorylation with ERK1/2 inhibitors. The effect of PPARγ on PCSK9 and LDLR expression remains unknown. In this study, we investigated the effects of PPARγ on PCSK9 and LDLR expression. At the cellular levels, PPARγ ligands induced PCSK9 mRNA and protein expression in HepG2 cells. PCSK9 expression was induced by inhibition of ERK1/2 activity but inhibited by ERK1/2 activation. The mutagenic study and promoter activity assay suggested that the induction of PCSK9 expression by ERK1/2 inhibitors was tightly linked to PPARγ dephosphorylation. However, PPARγ activation by ligands or ERK1/2 inhibitors induced hepatic LDLR expression. The promoter assay indicated that the induction of LDLR expression by PPARγ was sterol regulatory element-dependent because PPARγ enhanced sterol regulatory element-binding protein 2 (SREBP2) processing. In vivo, administration of pioglitazone or U0126 alone increased PCSK9 expression in mouse liver but had little effect on PCSK9 secretion. However, the co-treatment of pioglitazone and U0126 enhanced both PCSK9 expression and secretion. Similar to in vitro, the increased PCSK9 expression by pioglitazone and/or U0126 did not result in decreased LDLR expression and function. In contrast, pioglitazone and/or U0126 increased LDLR protein expression and membrane translocation, SREBP2 processing, and CYP7A1 expression in the liver, which led to decreased total and LDL cholesterol levels in serum. Our results indicate that although PPARγ activation increased PCSK9 expression, PPARγ activation induced LDLR and CYP7A1 expression that enhanced LDL cholesterol metabolism.Background: PCSK9 regulates cholesterol homeostasis by enhancing the LDLR protein degradation. The effects of PPARγ on PCSK9 and LDLR expression remain unknown.Results: PPARγ activation by ligands or dephosphorylation induces PCSK9 and LDLR expression and cholesterol metabolism.Conclusion: PPARγ is an important transcriptional factor in regulating PCSK9 and LDLR expression.Significance: We define a new signaling pathway that regulates PCSK9 and LDLR expression. Proprotein convertase subtilisin kexin type 9 (PCSK9) plays an important role in cholesterol homeostasis by enhancing the degradation of LDL receptor (LDLR) protein. Peroxisome proliferator-activated receptor γ (PPARγ) has been shown to be atheroprotective. PPARγ can be activated by ligands and/or dephosphorylation with ERK1/2 inhibitors. The effect of PPARγ on PCSK9 and LDLR expression remains unknown. In this study, we investigated the effects of PPARγ on PCSK9 and LDLR expression. At the cellular levels, PPARγ ligands induced PCSK9 mRNA and protein expression in HepG2 cells. PCSK9 expression was induced by inhibition of ERK1/2 activity but inhibited by ERK1/2 activation. The mutagenic study and promoter activity assay suggested that the induction of PCSK9 expression by ERK1/2 inhibitors was tightly linked to PPARγ dephosphorylation. However, PPARγ activation by ligands or ERK1/2 inhibitors induced hepatic LDLR expression. The promoter assay indicated that the induction of LDLR expression by PPARγ was sterol regulatory element-dependent because PPARγ enhanced sterol regulatory element-binding protein 2 (SREBP2) processing. In vivo, administration of pioglitazone or U0126 alone increased PCSK9 expression in mouse liver but had little effect on PCSK9 secretion. However, the co-treatment of pioglitazone and U0126 enhanced both PCSK9 expression and secretion. Similar to in vitro, the increased PCSK9 expression by pioglitazone and/or U0126 did not result in decreased LDLR expression and function. In contrast, pioglitazone and/or U0126 increased LDLR protein expression and membrane translocation, SREBP2 processing, and CYP7A1 expression in the liver, which led to decreased total and LDL cholesterol levels in serum. Our results indicate that although PPARγ activation increased PCSK9 expression, PPARγ activation induced LDLR and CYP7A1 expression that enhanced LDL cholesterol metabolism. Background: PCSK9 regulates cholesterol homeostasis by enhancing the LDLR protein degradation. The effects of PPARγ on PCSK9 and LDLR expression remain unknown. Results: PPARγ activation by ligands or dephosphorylation induces PCSK9 and LDLR expression and cholesterol metabolism. Conclusion: PPARγ is an important transcriptional factor in regulating PCSK9 and LDLR expression. Significance: We define a new signaling pathway that regulates PCSK9 and LDLR expression.

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)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,017
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
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 recherche0,0010,001
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 Opus0,012
Tête enseignante GPT0,232
Écart entre enseignants0,220 · 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.

Devis d'étudeExpérimental (laboratoire)
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

Citations87
Publié2012
Routes d'admission1
Résumé présentoui

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