Coordinated Regulation of UGT2B15 Expression by Long Noncoding RNA LINC00574 and hsa-miR-129-5p in HepaRG Cells

Yu, Dianke; Chen, Jing; Chen, Si; Xu, Lin; Wu, Leihong; Li, Dongying; Luo, Jiao; Yuan, Jing; Zhao, Yanjie; Knox, Bridgett; Tolleson, William H.; Wang, Xubing; Guo, Lei

doi:10.1124/dmd.119.090043

Cited by 7 publications

(4 citation statements)

References 38 publications

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“…Recent studies have suggested that lncRNAs are highly relevant to drug metabolism through the regulation of drug metabolizing enzyme genes [76][77][78]. In addition to HNF1α-AS1 and HNF4α-AS1, several other lncRNAs have also been identified in the regulation of expression of drug metabolizing enzyme genes, such as LINC00574 in the regulation of UGT2B15 expression, and contribution to susceptibility of drug-induced liver injury (DILI), for example LINC00844 [79,80]. These works have opened a novel area in the field of drug metabolism and DILI, which requires further studies to provide answers for some fundamental questions.…”

Section: Roles Of Hnf1α-as1 and Hnf4α-as1 In Physiologic Functions Including Drug Metabolismmentioning

confidence: 99%

The Roles of Long Noncoding RNAs HNF1α-AS1 and HNF4α-AS1 in Drug Metabolism and Human Diseases

Bao

Jiang

Zhong

2020

ncRNA

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Long noncoding RNAs (lncRNAs) are RNAs with a length of over 200 nucleotides that do not have protein-coding abilities. Recent studies suggest that lncRNAs are highly involved in physiological functions and diseases. lncRNAs HNF1α-AS1 and HNF4α-AS1 are transcripts of lncRNA genes HNF1α-AS1 and HNF4α-AS1, which are antisense lncRNA genes located in the neighborhood regions of the transcription factor (TF) genes HNF1α and HNF4α, respectively. HNF1α-AS1 and HNF4α-AS1 have been reported to be involved in several important functions in human physiological activities and diseases. In the liver, HNF1α-AS1 and HNF4α-AS1 regulate the expression and function of several drug-metabolizing cytochrome P450 (P450) enzymes, which also further impact P450-mediated drug metabolism and drug toxicity. In addition, HNF1α-AS1 and HNF4α-AS1 also play important roles in the tumorigenesis, progression, invasion, and treatment outcome of several cancers. Through interacting with different molecules, including miRNAs and proteins, HNF1α-AS1 and HNF4α-AS1 can regulate their target genes in several different mechanisms including miRNA sponge, decoy, or scaffold. The purpose of the current review is to summarize the identified functions and mechanisms of HNF1α-AS1 and HNF4α-AS1 and to discuss the future directions of research of these two lncRNAs.

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Section: Roles Of Hnf1α-as1 and Hnf4α-as1 In Physiologic Functions Including Drug Metabolismmentioning

confidence: 99%

The Roles of Long Noncoding RNAs HNF1α-AS1 and HNF4α-AS1 in Drug Metabolism and Human Diseases

Bao

Jiang

Zhong

2020

ncRNA

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“…The findings suggest a possible involvement in the regulation of mitochondrial function and ROS(Reactive Oxygen Species, ROS) levels and thus in the development of PD [ 57 ]. hsa-miR-129-5p has also been found to be differentially expressed in both AD and PD and is possibly involved in the development of Huntington’s disease, suggesting that this gene may be involved in a common pathogenic mechanism of neurodegenerative diseases, although the exact mechanism is not yet clear [ 58 ]. We also expect that future related studies can refer to the ceRNA network we constructed.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential immune-related hub genes in Parkinson’s disease based on machine learning and development and validation of a diagnostic classification model

Xin,

Niu,

Tian

et al. 2023

PLoS ONE

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Background Parkinson’s disease is the second most common neurodegenerative disease in the world. However, current diagnostic methods are still limited, and available treatments can only mitigate the symptoms of the disease, not reverse it at the root. The immune function has been identified as playing a role in PD, but the exact mechanism is unknown. This study aimed to search for potential immune-related hub genes in Parkinson’s disease, find relevant immune infiltration patterns, and develop a categorical diagnostic model. Methods We downloaded the GSE8397 dataset from the GEO database, which contains gene expression microarray data for 15 healthy human SN samples and 24 PD patient SN samples. Screening for PD-related DEGs using WGCNA and differential expression analysis. These PD-related DEGs were analyzed for GO and KEGG enrichment. Subsequently, hub genes (dld, dlk1, iars and ttd19) were screened by LASSO and mSVM-RFE machine learning algorithms. We used the ssGSEA algorithm to calculate and evaluate the differences in nigrostriatal immune cell types in the GSE8397 dataset. The association between dld, dlk1, iars and ttc19 and 28 immune cells was investigated. Using the GSEA and GSVA algorithms, we analyzed the biological functions associated with immune-related hub genes. Establishment of a ceRNA regulatory network for immune-related hub genes. Finally, a logistic regression model was used to develop a PD classification diagnostic model, and the accuracy of the model was verified in three independent data sets. The three independent datasets are GES49036 (containing 8 healthy human nigrostriatal tissue samples and 15 PD patient nigrostriatal tissue samples), GSE20292 (containing 18 healthy human nigrostriatal tissue samples and 11 PD patient nigrostriatal tissue samples) and GSE7621 (containing 9 healthy human nigrostriatal tissue samples and 16 PD patient nigrostriatal tissue samples). Results Ultimately, we screened for four immune-related Parkinson’s disease hub genes. Among them, the AUC values of dlk1, dld and ttc19 in GSE8397 and three other independent external datasets were all greater than 0.7, indicating that these three genes have a certain level of accuracy. The iars gene had an AUC value greater than 0.7 in GES8397 and one independent external data while the AUC values in the other two independent external data sets ranged between 0.5 and 0.7. These results suggest that iars also has some research value. We successfully constructed a categorical diagnostic model based on these four immune-related Parkinson’s disease hub genes, and the AUC values of the joint diagnostic model were greater than 0.9 in both GSE8397 and three independent external datasets. These results indicate that the categorical diagnostic model has a good ability to distinguish between healthy individuals and Parkinson’s disease patients. In addition, ceRNA networks reveal complex regulatory relationships based on immune-related hub genes. Conclusion In this study, four immune-related PD hub genes (dld, dlk1, iars and ttd19) were obtained. A reliable diagnostic model for PD classification was developed. This study provides algorithmic-level support to explore the immune-related mechanisms of PD and the prediction of immune-related drug targets.

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“…Among them, LINC00844 was significantly down-regulated in a concentration-dependent manner in response to APAP exposure, and it showed the positive relation with the mRNA levels of CYP3A4, 2E1, SULT2A1, PXR, and HNF4A (Li et al, 2020). Another lncRNA LINC00574 has been proved to coordinately regulate expression of a phase II drug-metabolizing enzyme UGT2B15 by interacting with miRNA miR-129 in HepaRG cells treated with APAP (Yu et al, 2020).…”

Section: Roles Of Histone Modifications In Induction Of Cyp Expressio...mentioning

confidence: 94%

Epigenetic Mechanisms Contribute to Intraindividual Variations of Drug Metabolism Mediated by Cytochrome P450 Enzymes

Jin

Zhong

2023

Drug Metab Dispos

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Significant interindividual and intraindividual variations on cytochrome P450 (CYP)-mediated drug metabolism exist in the general population globally. Genetic polymorphisms are one of the major contribution factors for interindividual variations, but epigenetic mechanisms mainly contribute to intraindividual variations, including DNA methylation, histone modifications, microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). The current review provides analysis of advanced knowledge in the last decade on contributions of epigenetic mechanisms to intraindividual variations on CYP-mediated drug metabolism in several situations, including (1) ontogeny, the developmental changes of CYP expression in individuals from neonates to adults; (2) increased activities of CYP enzymes induced by drug treatment; (3) increased activities of CYP enzymes in adult ages induced by drug treatment at neonate ages; and (4) decreased activities of CYP enzymes in individuals with drug-induced liver injury (DILI). Furthermore, current challenges, knowledge gaps, and future perspective of the epigenetic mechanisms in development of CYP pharmacoepigenetics are discussed. In conclusion, epigenetic mechanisms have been proven to contribute to intraindividual variations of drug metabolism mediated by CYP enzymes in age development, drug induction, and DILI conditions. The knowledge has helped understanding how intraindividual variation are generated. Future studies are needed to develop CYP-based pharmacoepigenetics to guide clinical applications for precision medicine with improved therapeutic efficacy and reduced risk of adverse drug reactions (ADRs) and toxicity.

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Coordinated Regulation of UGT2B15 Expression by Long Noncoding RNA LINC00574 and hsa-miR-129-5p in HepaRG Cells

Cited by 7 publications

References 38 publications

The Roles of Long Noncoding RNAs HNF1α-AS1 and HNF4α-AS1 in Drug Metabolism and Human Diseases

The Roles of Long Noncoding RNAs HNF1α-AS1 and HNF4α-AS1 in Drug Metabolism and Human Diseases

Identification of potential immune-related hub genes in Parkinson’s disease based on machine learning and development and validation of a diagnostic classification model

Epigenetic Mechanisms Contribute to Intraindividual Variations of Drug Metabolism Mediated by Cytochrome P450 Enzymes

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