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Record 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 on 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

Bibliographic record

VenueJournal of Biological Chemistry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsUniversity of Saskatchewan
FundersTianjin Science and Technology CommitteeNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsPCSK9LDL receptorProprotein convertasePeroxisome proliferator-activated receptorKexinChemistryBiologyDephosphorylationEndocrinologyReceptorInternal medicineCell biologyLipoproteinCholesterolPhosphorylationBiochemistryMedicinePhosphatase

Abstract

fetched live from 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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.001
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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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.

Study designBench or experimental
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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Citations87
Published2012
Admission routes1
Has abstractyes

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