scholarly journals Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models

2018 ◽  
Author(s):  
Cankut Çubuk ◽  
Marta R. Hidalgo ◽  
Alicia Amadoz ◽  
Kinza Rian ◽  
Francisco Salavert ◽  
...  
Keyword(s):  
Gene Expression ◽  
Metabolic Activity ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Therapeutic Interventions ◽  
Class Prediction ◽  
Web Based ◽  
Knock Out ◽  
Pathway Module ◽  
Metabolic Activities

AbstractBackgroundin spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling.Resultswe present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway module metabolic activities that can also be used for class prediction and in silico prediction of Knock-Out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer.ConclusionsMetabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.Metabolizer can be found at:http://metabolizer.babelomics.org.

MO262THE SINGLE-CELL TRANSCRIPTOMICS OF HUMAN IGA NEPHROPATHY

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Yong Zhong ◽  
Xiangcheng Xiao
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Signaling Pathways ◽  
Iga Nephropathy ◽  
Molecular Mechanisms ◽  
Mesangial Cells ◽  
Therapeutic Targets ◽  
Cell Types ◽  
Receptor Crosstalk ◽  
Overt Proteinuria

Abstract Background and Aims The exact molecular mechanisms underlying IgA nephropathy (IgAN) remains incompletely defined. Therefore, it is necessary to further elucidate the mechanism of IgA nephropathy and find novel therapeutic targets. Method Single-cell RNA sequencing (scRNA-seq) was applied to kidney biopsies from 4 IgAN and 1 control subjects to define the transcriptomic landscape at the single-cell resolution. Unsupervised clustering analysis of kidney specimens was used to identify distinct cell clusters. Differentially expressed genes and potential signaling pathways involved in IgAN were also identified. Results Our analysis identified 14 cell subsets in kidney biopsies from IgAN patients, and analyzed changing gene expression in distinct renal cell types. We found increased mesangial expression of several novel genes including MALAT1, GADD45B, SOX4 and EDIL3, which were related to proliferation and matrix accumulation and have not been reported in IgAN previously. The overexpressed genes in tubule cells of IgAN were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling and NOD-like receptor signaling. Moreover, the receptor-ligand crosstalk analysis revealed potential interactions between mesangial cells and other cells in IgAN. Specifically, IgAN with overt proteinuria displayed elevated genes participating in several signaling pathways which may be involved in pathogenesis of progression of IgAN. Conclusion The comprehensive analysis of kidney biopsy specimen demonstrated different gene expression profile, potential pathologic ligand-receptor crosstalk, signaling pathways in human IgAN. These results offer new insight into pathogenesis and identify new therapeutic targets for patients with IgA nephropathy.

scholarly journals Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yun Tang ◽  
Xiaobo Yang ◽  
Huaqing Shu ◽  
Yuan Yu ◽  
Shangwen Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Septic Shock ◽  
Acute Kidney Injury ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Kidney Injury ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Blood Samples ◽  
Potential Biomarkers

Abstract Background Sepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI). Methods Two gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI. Results We identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future. Conclusions Septic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

scholarly journals Identification of core genes and pathways in melanoma metastasis via bioinformatics analysis

2020 ◽  
Author(s):  
Yumei Li ◽  
Bifei Li ◽  
Fan Chen ◽  
Weiyu Shen ◽  
Vladimir L. Katanaev ◽  
...  
Keyword(s):  
Gene Expression ◽  
Metastatic Melanoma ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Primary Melanoma ◽  
Melanoma Cells ◽  
Receptor Interaction ◽  
Melanoma Metastasis ◽  
Hub Genes ◽  
Core Genes

Abstract Background Metastasis is the leading cause of melanoma mortality. Current therapies are rarely curative for metastatic melanoma, revealing the urgent need to identify more effective preventive and therapeutic targets. This study aimed to screen for the key core genes and molecular mechanisms related to the metastasis of melanoma. Methods Gene expression profile, GSE8401 including 31 primary melanoma and 52 metastatic melanoma clinical samples, was downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between metastatic melanoma and primary melanoma were screened using GEO2R. Assays of gene ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG) pathway and protein-protein interaction (PPI) were performed to visualize these DEGs through Database for Annotation, Visualization and Integrated Discovery (DAVID) software and Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape with Molecular Complex Detection (MCODE) plug-in tools. Top 10 genes with high degree were defined as hub genes. Furthermore, paired post-metastatic melanoma cells and pre-metastatic melanoma cells were established by experimental mouse model of melanoma metastasis to verify the expression of these hub genes. Results 424 DEGs between the metastatic melanoma and primary melanoma were screened, including 60 upregulated genes enriched in ECM-receptor interaction and progesterone-mediated oocyte maturation and 364 downregulated genes enriched in amoebiasis, melanogenesis, and ECM-receptor interaction. CDH1, EGFR, KRT5, COL17A1, KRT14, IVL, DSP, DSG1, FLG and CDK1 were defined as the hub genes. . In addition, paired post-metastatic melanoma cells (A375M) and pre-metastatic melanoma cells (A375) were established and qRT-PCR analysis confirmed the expression of the hub genes during melanoma metastasis. Conclusion This bioinformatic study has provided a deeper understanding of the molecular mechanisms of melanoma metastasis. KRT5, IVL and COL17A1 have emerged as possible biomarkers and therapeutic targets in metastasis of melanoma.

scholarly journals A functional landscape of chronic kidney disease entities from public transcriptomic data

2018 ◽  
Author(s):  
Ferenc Tajti ◽  
Christoph Kuppe ◽  
Asier Antoranz ◽  
Mahmoud M. Ibrahim ◽  
Hyojin Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Gene Expression Data ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Kidney Tissue ◽  
Therapeutic Targets ◽  
Expression Data ◽  
Disease Entities

AbstractTo develop efficient therapies and identify novel early biomarkers for chronic kidney disease an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in CKD origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for nine kidney disease entities that account for a majority of CKD worldwide. We included data from five distinct studies and compared glomerular gene expression profiles to that of non-tumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms and conditions, that we mitigated with a bespoke stringent procedure. This allowed us to perform a global transcriptome-based delineation of different kidney disease entities, obtaining a landscape of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. Furthermore, we derived functional insights by inferring activity of signaling pathways and transcription factors from the collected gene expression data, and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating e.g. that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in RPGN whereas not expressed in control kidney tissue. These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities, that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate this, we provide our results as a free interactive web application: https://saezlab.shinyapps.io/ckd_landscape/.Translational StatementChronic kidney disease is a combination of entities with different etiologies. We integrate and analyse transcriptomics analysis of glomerular from different entities to dissect their different pathophysiology, what might help to identify novel entity-specific therapeutic targets.

scholarly journals The Emerging Role of PIWI-Interacting RNAs (piRNAs) in Gastrointestinal Cancers: An Updated Perspective

Cancers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 202
Author(s):  
Ismael Riquelme ◽  
Pablo Pérez-Moreno ◽  
Pablo Letelier ◽  
Priscilla Brebi ◽  
Juan Carlos Roa
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Molecular Characteristics ◽  
Clinical Markers ◽  
Rna Transcripts ◽  
Gi Cancers ◽  
Tumor Types ◽  
Cumulative Evidence

Gastrointestinal (GI) cancers produce ~3.4 million related deaths worldwide, comprising 35% of all cancer-related deaths. The high mortality among GI cancers is due to late diagnosis, the presence of metastasis and drug resistance development. Additionally, current clinical markers do not adequately guide patient management, thereby new and more reliable biomarkers and therapeutic targets are still needed for these diseases. RNA-seq technology has allowed the discovery of new types of RNA transcripts including PIWI-interacting RNAs (piRNAs), which have particular characteristics that enable these molecules to act via diverse molecular mechanisms for regulating gene expression. Cumulative evidence has described the potential role of piRNAs in the development of several tumor types as a likely explanation for certain genomic abnormalities and signaling pathways’ deregulations observed in cancer. In addition, these piRNAs might be also proposed as promising diagnostic or prognostic biomarkers or as potential therapeutic targets in malignancies. This review describes important topics about piRNAs including their molecular characteristics, biosynthesis processes, gene expression silencing mechanisms, and the manner in which these transcripts have been studied in samples and cell lines of GI cancers to elucidate their implications in these diseases. Moreover, this article discusses the potential clinical usefulness of piRNAs as biomarkers and therapeutic targets in GI cancers.

scholarly journals RNA-Seq Reveals Different Gene Expression in Liver-Specific Prohibitin 1 Knock-Out Mice

2021 ◽  
Vol 12 ◽  
Author(s):  
Kyuwon Lee ◽  
Hyeonju Yu ◽  
Stephanie Shouse ◽  
Byungwhi Kong ◽  
Jihye Lee ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Regulatory Element ◽  
Global Gene Expression ◽  
Rna Seq ◽  
Knock Out ◽  
Forkhead Box M1 ◽  
Liver Injuries ◽  
Prohibitin 1 ◽  
Liver Tissues

Prohibitin 1 (PHB1) is an evolutionarily conserved and ubiquitously expressed protein that stabilizes mitochondrial chaperone. Our previous studies showed that liver-specific Phb1 deficiency induced liver injuries and aggravated lipopolysaccharide (LPS)-induced innate immune responses. In this study, we performed RNA-sequencing (RNA-seq) analysis with liver tissues to investigate global gene expression among liver-specific Phb1−/−, Phb1+/−, and WT mice, focusing on the differentially expressed (DE) genes between Phb1+/− and WT. When 78 DE genes were analyzed for biological functions, using ingenuity pathway analysis (IPA) tool, lipid metabolism-related genes, including insulin receptor (Insr), sterol regulatory element-binding transcription factor 1 (Srebf1), Srebf2, and SREBP cleavage-activating protein (Scap) appeared to be downregulated in liver-specific Phb1+/− compared with WT. Diseases and biofunctions analyses conducted by IPA verified that hepatic system diseases, including liver fibrosis, liver hyperplasia/hyperproliferation, and liver necrosis/cell death, which may be caused by hepatotoxicity, were highly associated with liver-specific Phb1 deficiency in mice. Interestingly, of liver disease-related 5 DE genes between Phb1+/− and WT, the mRNA expressions of forkhead box M1 (Foxm1) and TIMP inhibitor of metalloproteinase (Timp1) were matched with validation for RNA-seq in liver tissues and AML12 cells transfected with Phb1 siRNA. The results in this study provide additional insights into molecular mechanisms responsible for increasing susceptibility of liver injuries associated with hepatic Phb1.

scholarly journals Distinct Molecular Mechanisms Analysis of Obesity Based on Gene Expression Profiles

2020 ◽  
Author(s):  
Harish Joshi ◽  
Basavaraj Mallikarjunayya Vastrad ◽  
Nidhi Joshi ◽  
Chanabasayya Mallikarjunayya Vastrad
Keyword(s):  
Gene Expression ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Expression Profiles ◽  
Therapeutic Targets ◽  
Rank Aggregation ◽  
Receiver Operating Curve ◽  
Progression Rate ◽  
Hub Genes

Abstract Background Obesity is the most common metabolic disorder worldwide. Its progression rate has remained high in recent years. ObjectivesTherefore, the aim of this study was to diagnose important differentially expressed genes (DEGs) associated in its development, which may be used as novel biomarkers or potential therapeutic targets for obesity. MethodsThe gene expression profile of E-MTAB-6728 was downloaded from the database. After screening DEGs in each ArrayExpress dataset, we further used the robust rank aggregation method to diagnose 876 significant DEGs including 438 up regulated and 438 down regulated genes. Pathway enrichment analyses and Gene Ontology (GO) were performed by online tool ToppCluster. These DEGs were shown to be significantly enriched in different obesity related pathways and GO functions. Then, the mentha, miRNet and NetworkAnalyst databases were used to construct the protein–protein interaction network, target genes - miRNA regulatory network and target genes - TF regulatory network. The module analysis was performed by the PEWCC1 plug‐in of Cytoscape based on the whole PPI network.Results We finally filtered out HSPA8, ESR1, YWHAH, RPL14, SOD2, BTG2, LYZ and EFNA1 hub genes. Hub genes were validated by ICH analysis, Receiver operating curve (ROC) analysis and RT-PCR. The robust DEGs linked with the development of obesity were screened through the ArrayExpress database, and integrated bioinformatics analysis was conducted. ConclusionsOur study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for obesity.

Decreased Leukemia Initiating Cells in hdac1 Haploinsufficient T Cell Acute Lymphoblastic Leukemia

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1236-1236
Author(s):  
Margaret M. Pruitt ◽  
Sean C. McConnell ◽  
Anthony Restaino ◽  
Wilfredo Marin ◽  
Jill L. O. de Jong
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
T Cell ◽  
Tumor Cells ◽  
Molecular Mechanisms ◽  
Lymphoblastic Leukemia ◽  
Therapeutic Targets ◽  
Starting Point ◽  
Cell Acute Lymphoblastic Leukemia ◽  
New Therapeutic Targets

Abstract T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy that accounts for 15% of pediatric and 25% of adult ALL cases. While initial treatment of T-ALL has improved, relapse is common and is associated with a poor prognosis. As with other tumors, T-ALL is genetically heterogeneous and relapse is driven at least in part by a subpopulation of cells called leukemia initiating cells (LICs). Capable of regrowing the entire tumor from a single cell, failure to eliminate these LICs is hypothesized to be the major determinant of relapse. Therefore understanding the genetic mechanisms that drive LICs may lead to new therapeutic targets that are likely to enhance rates of cure. The data presented here indicate that histone deacetylase 1 (hdac1) is an important regulator of LICs in T-ALL. Histone deacetylases (hdacs) modify chromatin structure and regulate gene expression by removing acetyl groups from histones and other proteins. As hdacs are aberrantly expressed in hematopoietic malignancies, and hdac inhibitors are used to treat some cancers, we hypothesized that hdac1 might play a role in leukemogenesis. To explore this question, we generated T cell acute lymphoblastic leukemias by overexpressing the murine c-Myc oncogene and the fluorochrome mCherry under the rag2 promoter in hdac1 haploinsufficient zebrafish. Tumor incidence and latency were not significantly different for hdac1+/- and wild type (WT) tumors. Mean tumor latency was 42.3 days post fertilization (dpf) for hdac1+/- fish and 47.9 dpf for their WT siblings. Likewise overall survival was not different. Mean survival was 58.0 dpf for hdac1+/- fish, and 64.6 dpf for WT fish. In contrast, when primary leukemia cells were transplanted into syngeneic recipient fish, the tumor cells from hdac1 haploinsufficient fish grew at a slower rate when compared to tumor cells from WT fish. After transplanting 1x105 primary WT or hdac1+/- tumor cells intraperitoneally into syngeneic zebrafish recipients, the transplanted WT tumors grew more aggressively compared to the hdac1+/- tumors. By 21 days post transplant, 92% of the WT tumors (n=22 of 24) had spread from the site of injection into the thymus and other organs, while most of the hdac1+/- tumors were only growing at the site of injection. Only 8.3% (n=1 of 12) of the hdac1+/- tumors had spread past the local injection site at this time point. We found that the slower rate of growth was not due to differences in proliferation, as determined by EdU incorporation. Hdac1+/- tumors had a mean percentage of EdU incorporation of 6.0 ± 4.0% (n=12), and WT tumors had 6.4 ± 4.4% (n=7); (p=0.8). In contrast, limit dilution transplant assays showed a higher frequency of leukemia initiating cells in the WT tumors (1 in 44 cells) compared with the hdac1+/- tumors (1 in 135 cells) (p<0.05). RNA-sequencing and qPCR analyses have been employed to determine gene expression differences between hdac1+/- and WT tumors. Transcriptome analysis has identified 1731 genes that are differentially expressed (p<1x10-5), 674 of which have at least a 5-fold difference in expression. Of these genes, 261 exhibited decreased expression in hdac1+/- tumors, and 413 exhibited increased expression in hdac1+/- tumors. Experiments are ongoing to elucidate the core molecular mechanisms that inhibit LICs in hdac1 haploinsufficient cells. These results provide a starting point to identify new therapeutic targets for T-ALL. Disclosures de Jong: National Medical Consultants, P.C.: Consultancy.

Inflammageing in the cardiovascular system: mechanisms, emerging targets, and novel therapeutic strategies

2020 ◽  
Vol 134 (17) ◽  
pp. 2243-2262
Author(s):  
Danlin Liu ◽  
Gavin Richardson ◽  
Fehmi M. Benli ◽  
Catherine Park ◽  
João V. de Souza ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Cardiovascular System ◽  
Nlrp3 Inflammasome ◽  
Molecular Mechanisms ◽  
Molecular Targets ◽  
Therapeutic Interventions ◽  
Low Grade ◽  
Cardiovascular Research ◽  
Inflammatory Processes ◽  
Ach Receptors

Abstract In the elderly population, pathological inflammation has been associated with ageing-associated diseases. The term ‘inflammageing’, which was used for the first time by Franceschi and co-workers in 2000, is associated with the chronic, low-grade, subclinical inflammatory processes coupled to biological ageing. The source of these inflammatory processes is debated. The senescence-associated secretory phenotype (SASP) has been proposed as the main origin of inflammageing. The SASP is characterised by the release of inflammatory cytokines, elevated activation of the NLRP3 inflammasome, altered regulation of acetylcholine (ACh) nicotinic receptors, and abnormal NAD+ metabolism. Therefore, SASP may be ‘druggable’ by small molecule therapeutics targeting those emerging molecular targets. It has been shown that inflammageing is a hallmark of various cardiovascular diseases, including atherosclerosis, hypertension, and adverse cardiac remodelling. Therefore, the pathomechanism involving SASP activation via the NLRP3 inflammasome; modulation of NLRP3 via α7 nicotinic ACh receptors; and modulation by senolytics targeting other proteins have gained a lot of interest within cardiovascular research and drug development communities. In this review, which offers a unique view from both clinical and preclinical target-based drug discovery perspectives, we have focused on cardiovascular inflammageing and its molecular mechanisms. We have outlined the mechanistic links between inflammageing, SASP, interleukin (IL)-1β, NLRP3 inflammasome, nicotinic ACh receptors, and molecular targets of senolytic drugs in the context of cardiovascular diseases. We have addressed the ‘druggability’ of NLRP3 and nicotinic α7 receptors by small molecules, as these proteins represent novel and exciting targets for therapeutic interventions targeting inflammageing in the cardiovascular system and beyond.

The Mechanisms Behind the Biological Activity of Flavonoids

2019 ◽  
Vol 26 (39) ◽  
pp. 6976-6990 ◽  
Author(s):  
Ana María González-Paramás ◽  
Begoña Ayuda-Durán ◽  
Sofía Martínez ◽  
Susana González-Manzano ◽  
Celestino Santos-Buelga
Keyword(s):  
Gene Expression ◽  
Biological Activity ◽  
Phenolic Compounds ◽  
Intracellular Signaling ◽  
Molecular Mechanisms ◽  
Radical Scavenging ◽  
Model Organism ◽  
Stress Theory ◽  
Radical Scavenging Properties

: Flavonoids are phenolic compounds widely distributed in the human diet. Their intake has been associated with a decreased risk of different diseases such as cancer, immune dysfunction or coronary heart disease. However, the knowledge about the mechanisms behind their in vivo activity is limited and still under discussion. For years, their bioactivity was associated with the direct antioxidant and radical scavenging properties of phenolic compounds, but nowadays this assumption is unlikely to explain their putative health effects, or at least to be the only explanation for them. New hypotheses about possible mechanisms have been postulated, including the influence of the interaction of polyphenols and gut microbiota and also the possibility that flavonoids or their metabolites could modify gene expression or act as potential modulators of intracellular signaling cascades. This paper reviews all these topics, from the classical view as antioxidants in the context of the Oxidative Stress theory to the most recent tendencies related with the modulation of redox signaling pathways, modification of gene expression or interactions with the intestinal microbiota. The use of C. elegans as a model organism for the study of the molecular mechanisms involved in biological activity of flavonoids is also discussed.

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