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Leask MP, Crișan TO, Ji A, Matsuo H, Köttgen A, Merriman TR. The pathogenesis of gout: molecular insights from genetic, epigenomic and transcriptomic studies. Nat Rev Rheumatol 2024; 20:510-523. [PMID: 38992217 DOI: 10.1038/s41584-024-01137-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/11/2024] [Indexed: 07/13/2024]
Abstract
The pathogenesis of gout involves a series of steps beginning with hyperuricaemia, followed by the deposition of monosodium urate crystal in articular structures and culminating in an innate immune response, mediated by the NLRP3 inflammasome, to the deposited crystals. Large genome-wide association studies (GWAS) of serum urate levels initially identified the genetic variants with the strongest effects, mapping mainly to genes that encode urate transporters in the kidney and gut. Other GWAS highlighted the importance of uncommon genetic variants. More recently, genetic and epigenetic genome-wide studies have revealed new pathways in the inflammatory process of gout, including genetic associations with epigenomic modifiers. Epigenome-wide association studies are also implicating epigenomic remodelling in gout, which perhaps regulates the responsiveness of the innate immune system to monosodium urate crystals. Notably, genes implicated in gout GWAS do not include those encoding components of the NLRP3 inflammasome itself, but instead include genes encoding molecules involved in its regulation. Knowledge of the molecular mechanisms underlying gout has advanced through the translation of genetic associations into specific molecular mechanisms. Notable examples include ABCG2, HNF4A, PDZK1, MAF and IL37. Current genetic studies are dominated by participants of European ancestry; however, studies focusing on other population groups are discovering informative population-specific variants associated with gout.
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Affiliation(s)
- Megan P Leask
- Department of Physiology, University of Otago, Dunedin, Aotearoa, New Zealand
- Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Tania O Crișan
- Department of Medical Genetics, "Iuliu Haţieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Aichang Ji
- Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China
| | - Hirotaka Matsuo
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Saitama, Japan
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Tony R Merriman
- Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL, USA.
- Department of Microbiology and Immunology, University of Otago, Dunedin, Aotearoa, New Zealand.
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2
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Merlo Pich LM, Ziogas A, Netea MG. Genetic and epigenetic dysregulation of innate immune mechanisms in autoinflammatory diseases. FEBS J 2024. [PMID: 38468589 DOI: 10.1111/febs.17116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 01/17/2024] [Accepted: 03/01/2024] [Indexed: 03/13/2024]
Abstract
Dysregulation and hyperactivation of innate immune responses can lead to the onset of systemic autoinflammatory diseases. Monogenic autoinflammatory diseases are caused by inborn genetic errors and based on molecular mechanisms at play, can be divided into inflammasomopathies, interferonopathies, relopathies, protein misfolding, and endogenous antagonist deficiencies. On the other hand, more common autoinflammatory diseases are multifactorial, with both genetic and non-genetic factors playing an important role. During the last decade, long-term memory characteristics of innate immune responses have been described (also called trained immunity) that in physiological conditions provide enhanced host protection from pathogenic re-infection. However, if dysregulated, induction of trained immunity can become maladaptive, perpetuating chronic inflammatory activation. Here, we describe the mechanisms of genetic and epigenetic dysregulation of the innate immune system and maladaptive trained immunity that leads to the onset and perpetuation of the most common and recently described systemic autoinflammatory diseases.
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Affiliation(s)
- Laura M Merlo Pich
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Athanasios Ziogas
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mihai G Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
- Department for Immunology and Metabolism, Life and Medical Sciences Institute (LIMES), University of Bonn, Germany
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Zhang X, Hu Y, Vandenhoudt RE, Yan C, Marconi VC, Cohen MH, Wang Z, Justice AC, Aouizerat BE, Xu K. Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts. PLoS Pathog 2024; 20:e1012063. [PMID: 38466776 PMCID: PMC10957090 DOI: 10.1371/journal.ppat.1012063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 03/21/2024] [Accepted: 02/20/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Epigenome-wide association studies (EWAS) have identified CpG sites associated with HIV infection in blood cells in bulk, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. In this study, we aim to identify differentially methylated CpG sites for HIV infection in immune cell types: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes. METHODS Applying a computational deconvolution method, we performed a cell-type based EWAS for HIV infection in three independent cohorts (Ntotal = 1,382). DNA methylation in blood or in peripheral blood mononuclear cells (PBMCs) was profiled by an array-based method and then deconvoluted by Tensor Composition Analysis (TCA). The TCA-computed CpG methylation in each cell type was first benchmarked by bisulfite DNA methylation capture sequencing in a subset of the samples. Cell-type EWAS of HIV infection was performed in each cohort separately and a meta-EWAS was conducted followed by gene set enrichment analysis. RESULTS The meta-analysis unveiled a total of 2,021 cell-type unique significant CpG sites for five inferred cell types. Among these inferred cell-type unique CpG sites, the concordance rate in the three cohorts ranged from 96% to 100% in each cell type. Cell-type level meta-EWAS unveiled distinct patterns of HIV-associated differential CpG methylation, where 74% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of unique HIV-associated CpG sites (N = 1,624) compared to any other cell type. Genes harboring significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CD4+ T-cells: NLRC5, CX3CR1, B cells: IFI44L, NK cells: IL12R, monocytes: IRF7), and in oncogenesis (e.g. CD4+ T-cells: BCL family, PRDM16, monocytes: PRDM16, PDCD1LG2). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis that were enriched among interferon-α and -γ, TNF-α, inflammatory response, and apoptotic pathways. CONCLUSION Our findings uncovered computationally inferred cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding HIV pathogenesis.
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Affiliation(s)
- Xinyu Zhang
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
| | - Ying Hu
- Center for Biomedical Information and Information Technology, National Cancer Institute, Rockville, Maryland, United States of America
| | - Ral E. Vandenhoudt
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
| | - Chunhua Yan
- Center for Biomedical Information and Information Technology, National Cancer Institute, Rockville, Maryland, United States of America
| | - Vincent C. Marconi
- Division of Infectious Diseases, Emory University School of Medicine and Department of Global Health, Rollins School of Public Health, Emory University, Georgia, United States of America
- Atlanta Veterans Affairs Healthcare System, Decatur, Georgia, United States of America
| | - Mardge H. Cohen
- Department of Medicine, Stroger Hospital of Cook County, Chicago, Illinois, United States of America
| | - Zuoheng Wang
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Amy C. Justice
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Bradley E. Aouizerat
- Translational Research Center, College of Dentistry, New York University, New York, New York, United States of America
- Department of Oral and Maxillofacial Surgery, College of Dentistry, New York University, New York, New York, United States of America
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
- Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut, United States of America
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de Lima JD, de Paula AGP, Yuasa BS, de Souza Smanioto CC, da Cruz Silva MC, Dos Santos PI, Prado KB, Winter Boldt AB, Braga TT. Genetic and Epigenetic Regulation of the Innate Immune Response to Gout. Immunol Invest 2023; 52:364-397. [PMID: 36745138 DOI: 10.1080/08820139.2023.2168554] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Gout is a disease caused by uric acid (UA) accumulation in the joints, causing inflammation. Two UA forms - monosodium urate (MSU) and soluble uric acid (sUA) have been shown to interact physically with inflammasomes, especially with the nod-like receptor (NLR) family pyrin domain containing 3 (NLRP3), albeit the role of the immune response to UA is poorly understood, given that asymptomatic hyperuricemia does also exist. Macrophage phagocytosis of UA activate NLRP3, lead to cytokines release, and ultimately, lead to chemoattract neutrophils and lymphocytes to the gout flare joint spot. Genetic variants of inflammasome genes and of genes encoding their molecular partners may influence hyperuricemia and gout susceptibility, while also influencing other comorbidities such as metabolic syndrome and cardiovascular diseases. In this review, we summarize the inflammatory responses in acute and chronic gout, specifically focusing on innate immune cell mechanisms and genetic and epigenetic characteristics of participating molecules. Unprecedently, a novel UA binding protein - the neuronal apoptosis inhibitor protein (NAIP) - is suggested as responsible for the asymptomatic hyperuricemia paradox.Abbreviation: β2-integrins: leukocyte-specific adhesion molecules; ABCG2: ATP-binding cassete family/breast cancer-resistant protein; ACR: American college of rheumatology; AIM2: absent in melanoma 2, type of pattern recognition receptor; ALPK1: alpha-protein kinase 1; ANGPTL2: angiopoietin-like protein 2; ASC: apoptosis-associated speck-like protein; BIR: baculovirus inhibitor of apoptosis protein repeat; BIRC1: baculovirus IAP repeat-containing protein 1; BIRC2: baculoviral IAP repeat-containing protein 2; C5a: complement anaphylatoxin; cAMP: cyclic adenosine monophosphate; CARD: caspase activation and recruitment domains; CARD8: caspase recruitment domain-containing protein 8; CASP1: caspase 1; CCL3: chemokine (C-C motif) ligand 3; CD14: cluster of differentiation 14; CD44: cluster of differentiation 44; Cg05102552: DNA-methylation site, usually cytosine followed by guanine nucleotides; contains arbitrary identification code; CIDEC: cell death-inducing DNA fragmentation factor-like effector family; CKD: chronic kidney disease; CNV: copy number variation; CPT1A: carnitine palmitoyl transferase - type 1a; CXCL1: chemokine (CXC motif) ligand 1; DAMPs: damage associated molecular patterns; DC: dendritic cells; DNMT(1): maintenance DNA methyltransferase; eQTL: expression quantitative trait loci; ERK1: extracellular signal-regulated kinase 1; ERK2: extracellular signal-regulated kinase 2; EULAR: European league against rheumatism; GMCSF: granulocyte-macrophage colony-stimulating factor; GWAS: global wide association studies; H3K27me3: tri-methylation at the 27th lysine residue of the histone h3 protein; H3K4me1: mono-methylation at the 4th lysine residue of the histone h3 protein; H3K4me3: tri-methylation at the 4th lysine residue of the histone h3 protein; HOTAIR: human gene located between hoxc11 and hoxc12 on chromosome 12; IκBα: cytoplasmatic protein/Nf-κb transcription inhibitor; IAP: inhibitory apoptosis protein; IFNγ: interferon gamma; IL-1β: interleukin 1 beta; IL-12: interleukin 12; IL-17: interleukin 17; IL18: interleukin 18; IL1R1: interleukin-1 receptor; IL-1Ra: interleukin-1 receptor antagonist; IL-22: interleukin 22; IL-23: interleukin 23; IL23R: interleukin 23 receptor; IL-33: interleukin 33; IL-6: interleukin 6; IMP: inosine monophosphate; INSIG1: insulin-induced gene 1; JNK1: c-jun n-terminal kinase 1; lncRNA: long non-coding ribonucleic acid; LRR: leucine-rich repeats; miR: mature non-coding microRNAs measuring from 20 to 24 nucleotides, animal origin; miR-1: miR followed by arbitrary identification code; miR-145: miR followed by arbitrary identification code; miR-146a: miR followed by arbitrary identification code, "a" stands for mir family; "a" family presents similar mir sequence to "b" family, but different precursors; miR-20b: miR followed by arbitrary identification code; "b" stands for mir family; "b" family presents similar mir sequence to "a" family, but different precursors; miR-221: miR - followed by arbitrary identification code; miR-221-5p: miR followed by arbitrary identification code; "5p" indicates different mature miRNAs generated from the 5' arm of the pre-miRNA hairpin; miR-223: miR followed by arbitrary identification code; miR-223-3p: mir followed by arbitrary identification code; "3p" indicates different mature miRNAs generated from the 3' arm of the pre-miRNA hairpin; miR-22-3p: miR followed by arbitrary identification code, "3p" indicates different mature miRNAs generated from the 3' arm of the pre-miRNA hairpin; MLKL: mixed lineage kinase domain-like pseudo kinase; MM2P: inductor of m2-macrophage polarization; MSU: monosodium urate; mTOR: mammalian target of rapamycin; MyD88: myeloid differentiation primary response 88; n-3-PUFAs: n-3-polyunsaturated fatty-acids; NACHT: acronym for NAIP (neuronal apoptosis inhibitor protein), C2TA (MHC class 2 transcription activator), HET-E (incompatibility locus protein from podospora anserina) and TP1 (telomerase-associated protein); NAIP: neuronal apoptosis inhibitory protein (human); Naip1: neuronal apoptosis inhibitory protein type 1 (murine); Naip5: neuronal apoptosis inhibitory protein type 5 (murine); Naip6: neuronal apoptosis inhibitory protein type 6 (murine); NBD: nucleotide-binding domain; Nek7: smallest NIMA-related kinase; NET: neutrophil extracellular traps; Nf-κB: nuclear factor kappa-light-chain-enhancer of activated b cells; NFIL3: nuclear-factor, interleukin 3 regulated protein; NIIMA: network of immunity in infection, malignancy, and autoimmunity; NLR: nod-like receptor; NLRA: nod-like receptor NLRA containing acidic domain; NLRB: nod-like receptor NLRA containing BIR domain; NLRC: nod-like receptor NLRA containing CARD domain; NLRC4: nod-like receptor family CARD domain containing 4; NLRP: nod-like receptor NLRA containing PYD domain; NLRP1: nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain containing 1; NLRP12: nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain containing 12; NLRP3: nod-like receptor family pyrin domain containing 3; NOD2: nucleotide-binding oligomerization domain; NRBP1: nuclear receptor-binding protein; Nrf2: nuclear factor erythroid 2-related factor 2; OR: odds ratio; P2X: group of membrane ion channels activated by the binding of extracellular; P2X7: p2x purinoceptor 7 gene; p38: member of the mitogen-activated protein kinase family; PAMPs: pathogen associated molecular patters; PBMC: peripheral blood mononuclear cells; PGGT1B: geranylgeranyl transferase type-1 subunit beta; PHGDH: phosphoglycerate dehydrogenase; PI3-K: phospho-inositol; PPARγ: peroxisome proliferator-activated receptor gamma; PPARGC1B: peroxisome proliferative activated receptor, gamma, coactivator 1 beta; PR3: proteinase 3 antigen; Pro-CASP1: inactive precursor of caspase 1; Pro-IL1β: inactive precursor of interleukin 1 beta; PRR: pattern recognition receptors; PYD: pyrin domain; RAPTOR: regulatory associated protein of mTOR complex 1; RAS: renin-angiotensin system; REDD1: regulated in DNA damage and development 1; ROS: reactive oxygen species; rs000*G: single nuclear polymorphism, "*G" is related to snp where replaced nucleotide is guanine, usually preceded by an id number; SLC2A9: solute carrier family 2, member 9; SLC7A11: solute carrier family 7, member 11; SMA: smooth muscular atrophy; Smac: second mitochondrial-derived activator of caspases; SNP: single nuclear polymorphism; Sp3: specificity protein 3; ST2: serum stimulation-2; STK11: serine/threonine kinase 11; sUA: soluble uric acid; Syk: spleen tyrosine kinase; TAK1: transforming growth factor beta activated kinase; Th1: type 1 helper T cells; Th17: type 17 helper T cells; Th2: type 2 helper T cells; Th22: type 22 helper T cells; TLR: tool-like receptor; TLR2: toll-like receptor 2; TLR4: toll-like receptor 4; TNFα: tumor necrosis factor alpha; TNFR1: tumor necrosis factor receptor 1; TNFR2: tumor necrosis factor receptor 2; UA: uric acid; UBAP1: ubiquitin associated protein; ULT: urate-lowering therapy; URAT1: urate transporter 1; VDAC1: voltage-dependent anion-selective channel 1.
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Affiliation(s)
- Jordana Dinorá de Lima
- Microbiology, Parasitology and Pathology Program, Universidade Federal do Parana (UFPR), Curitiba, Brazil
| | | | - Bruna Sadae Yuasa
- Microbiology, Parasitology and Pathology Program, Universidade Federal do Parana (UFPR), Curitiba, Brazil
| | | | - Maria Clara da Cruz Silva
- Microbiology, Parasitology and Pathology Program, Universidade Federal do Parana (UFPR), Curitiba, Brazil
| | | | - Karin Braun Prado
- Genetics Program, Universidade Federal do Parana (UFPR), Curitiba, Brazil
| | - Angelica Beate Winter Boldt
- Program of Internal Medicine, Universidade Federal do Parana (UFPR), Curitiba, Brazil
- Genetics Program, Universidade Federal do Parana (UFPR), Curitiba, Brazil
| | - Tárcio Teodoro Braga
- Microbiology, Parasitology and Pathology Program, Universidade Federal do Parana (UFPR), Curitiba, Brazil
- Biosciences and Biotechnology Program, Instituto Carlos Chagas (ICC), Fiocruz-Parana, Brazil
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Ferrari L, Monti P, Favero C, Carugno M, Tarantini L, Maggioni C, Bonzini M, Pesatori AC, Bollati V. Association between night shift work and methylation of a subset of immune-related genes. Front Public Health 2023; 10:1083826. [PMID: 36711387 PMCID: PMC9877629 DOI: 10.3389/fpubh.2022.1083826] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 12/22/2022] [Indexed: 01/13/2023] Open
Abstract
Introduction Night shift (NS) work has been associated with an increased risk of different conditions characterized by altered inflammatory and immune responses, such as cardio-metabolic and infectious diseases, cancer, and obesity. Epigenetic modifications, such as DNA methylation, might mirror alterations in biological processes that are influenced by NS work. Methods The present study was conducted on 94 healthy female workers with different working schedules and aimed at identifying whether NS was associated with plasmatic concentrations of the inflammatory proteins NLRP3 and TNF-alpha, as well as with DNA methylation levels of ten human endogenous retroviral (HERV) sequences, and nine genes selected for their role in immune and inflammatory processes. We also explored the possible role of the body mass index (BMI) as an additional susceptibility factor that might influence the effects of NS work on the tested epigenetic modifications. Results and discussion We observed a positive association between NS and NLRP3 levels (p-value 0.0379). Moreover, NS workers retained different methylation levels for ERVFRD-1 (p-value = 0.0274), HERV-L (p-value = 0.0377), and HERV-P (p-value = 0.0140) elements, and for BIRC2 (p-value = 0.0460), FLRT3 (p-value = 0.0422), MIG6 (p-value = 0.0085), and SIRT1 (p-value = 0.0497) genes. We also observed that the BMI modified the relationship between NS and the methylation of ERVE, HERV-L, and ERVW-1 elements. Overall, our results suggest that HERV methylation could pose as a promising biomolecular sensor to monitor not only the effect of NS work but also the cumulative effect of multiple stressors.
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Affiliation(s)
- Luca Ferrari
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy,Occupational Health Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy,*Correspondence: Luca Ferrari ✉
| | - Paola Monti
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy
| | - Chiara Favero
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy
| | - Michele Carugno
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy,Occupational Health Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Letizia Tarantini
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy
| | - Cristina Maggioni
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy
| | - Matteo Bonzini
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy,Occupational Health Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Angela Cecilia Pesatori
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy,Occupational Health Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Valentina Bollati
- EPIGET Lab, Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, Milan, Italy,Occupational Health Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
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Hu H, Guo L, Overholser J, Wang X. Mitochondrial VDAC1: A Potential Therapeutic Target of Inflammation-Related Diseases and Clinical Opportunities. Cells 2022; 11:cells11193174. [PMID: 36231136 PMCID: PMC9562648 DOI: 10.3390/cells11193174] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/27/2022] [Accepted: 09/30/2022] [Indexed: 12/03/2022] Open
Abstract
The multifunctional protein, voltage-dependent anion channel 1 (VDAC1), is located on the mitochondrial outer membrane. It is a pivotal protein that maintains mitochondrial function to power cellular bioactivities via energy generation. VDAC1 is involved in regulating energy production, mitochondrial oxidase stress, Ca2+ transportation, substance metabolism, apoptosis, mitochondrial autophagy (mitophagy), and many other functions. VDAC1 malfunction is associated with mitochondrial disorders that affect inflammatory responses, resulting in an up-regulation of the body’s defensive response to stress stimulation. Overresponses to inflammation may cause chronic diseases. Mitochondrial DNA (mtDNA) acts as a danger signal that can further trigger native immune system activities after its secretion. VDAC1 mediates the release of mtDNA into the cytoplasm to enhance cytokine levels by activating immune responses. VDAC1 regulates mitochondrial Ca2+ transportation, lipid metabolism and mitophagy, which are involved in inflammation-related disease pathogenesis. Many scientists have suggested approaches to deal with inflammation overresponse issues via specific targeting therapies. Due to the broad functionality of VDAC1, it may become a useful target for therapy in inflammation-related diseases. The mechanisms of VDAC1 and its role in inflammation require further exploration. We comprehensively and systematically summarized the role of VDAC1 in the inflammatory response, and hope that our research will lead to novel therapeutic strategies that target VDAC1 in order to treat inflammation-related disorders.
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Affiliation(s)
- Hang Hu
- Inflammation & Allergic Diseases Research Unit, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
- Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Linlin Guo
- Department of Obstetrics and Gynecology, The Ohio State University Wexner Medical Center at The Ohio State University, Columbus, OH 43210, USA
- Correspondence: (L.G.); (X.W.)
| | - Jay Overholser
- Department of Obstetrics and Gynecology, The Ohio State University Wexner Medical Center at The Ohio State University, Columbus, OH 43210, USA
| | - Xing Wang
- Inflammation & Allergic Diseases Research Unit, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
- Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
- Correspondence: (L.G.); (X.W.)
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Hu CM, Peng J, Lv L, Wang XH, Huo JR, Liu DL. MiR-196a promotes the proliferation and migration of esophageal cancer via the UHRF2/TET2 axis. Mol Cell Biochem 2022; 477:537-547. [PMID: 34826027 DOI: 10.1007/s11010-021-04301-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 11/08/2021] [Indexed: 12/19/2022]
Abstract
The aim of this study was to investigate the functions and molecular mechanism of miR-196a in esophageal cancer (EC). miR-196a as well as UHRF2 and TET2 mRNA and protein levels in EC tissues and cells were detected using quantitative real-time PCR or western blot, respectively. Cell proliferation was evaluated via MTT assay. Transwell assays were used to detect cell migration. In addition, the targeted relationship between miR-196a and UHRF2 was assessed through a dual luciferase reporter assay. Enzyme-linked immunosorbent assay was performed to detect the levels of the cytosine intermediates 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). We found increased miR-196a expression in EC tissues and cells but decreased UHRF2 and TET2 expression. Next, functional experiments showed that knockdown of miR-196a or UHRF2 overexpression suppress EC cell proliferation and migration. miR-196a negatively regulates TET2 expression by directly targeting UHRF2. UHRF2 overexpression decreased 5mC levels but increased 5hmC levels. Furthermore, TET2 downregulation reversed the functions of miR-196a inhibition on EC cell proliferation and migration. Collectively, our study suggested that miR-196a was closely related to the progression of EC possibly by regulating the UHRF2/TET2 axis. Thus, miR-196a represents a potential new EC therapeutic target.
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Affiliation(s)
- Chang-Mei Hu
- Department of Gastroenterology, Second Xiangya Hospital, Central South University, No. 139, Mid RenMin Rd., Changsha, 410011, Hunan Province, People's Republic of China.
| | - Jie Peng
- Department of Haematology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan Province, People's Republic of China
| | - Liang Lv
- Department of Gastroenterology, Second Xiangya Hospital, Central South University, No. 139, Mid RenMin Rd., Changsha, 410011, Hunan Province, People's Republic of China
| | - Xue-Hong Wang
- Department of Gastroenterology, Second Xiangya Hospital, Central South University, No. 139, Mid RenMin Rd., Changsha, 410011, Hunan Province, People's Republic of China
| | - Ji-Rong Huo
- Department of Gastroenterology, Second Xiangya Hospital, Central South University, No. 139, Mid RenMin Rd., Changsha, 410011, Hunan Province, People's Republic of China
| | - De-Liang Liu
- Department of Gastroenterology, Second Xiangya Hospital, Central South University, No. 139, Mid RenMin Rd., Changsha, 410011, Hunan Province, People's Republic of China
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Badii M, Gaal O, Popp RA, Crisan TO, Joosten LAB. Trained immunity and inflammation in rheumatic diseases. Joint Bone Spine 2022; 89:105364. [DOI: 10.1016/j.jbspin.2022.105364] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 02/01/2022] [Accepted: 02/09/2022] [Indexed: 11/27/2022]
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Georgel PT, Georgel P. Where Epigenetics Meets Food Intake: Their Interaction in the Development/Severity of Gout and Therapeutic Perspectives. Front Immunol 2021; 12:752359. [PMID: 34603340 PMCID: PMC8484966 DOI: 10.3389/fimmu.2021.752359] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 08/31/2021] [Indexed: 01/02/2023] Open
Abstract
Gout is the most frequent form of inflammatory arthritis in the world. Its prevalence is particularly elevated in specific geographical areas such as in the Oceania/Pacific region and is rising in the US, Europe, and Asia. Gout is a severe and painful disease, in which co-morbidities are responsible for a significant reduction in life expectancy. However, gout patients remain ostracized because the disease is still considered "self-inflicted", as a result of unhealthy lifestyle and excessive food and alcohol intake. While the etiology of gout flares is clearly associated with the presence of monosodium urate (MSU) crystal deposits, several major questions remain unanswered, such as the relationships between diet, hyperuricemia and gout flares or the mechanisms by which urate induces inflammation. Recent advances have identified gene variants associated with gout incidence. Nevertheless, genetic origins of gout combined to diet-related possible uric acid overproduction account for the symptoms in only a minor portion of patients. Hence, additional factors must be at play. Here, we review the impact of epigenetic mechanisms in which nutrients (such as ω-3 polyunsaturated fatty acids) and/or dietary-derived metabolites (like urate) trigger anti/pro-inflammatory responses that may participate in gout pathogenesis and severity. We propose that simple dietary regimens may be beneficial to complement therapeutic management or contribute to the prevention of flares in gout patients.
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Affiliation(s)
- Philippe T Georgel
- Department of Biological Sciences, Cell Differentiation and Development Center, Joan C. Edwards School of Medicine, Byrd Biotechnology Science Center, Marshall University, Huntington, WV, United States
| | - Philippe Georgel
- Laboratoire d'ImmunoRhumatologie Moléculaire, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR_S 1109, Institut thématique interdisciplinaire (ITI) de Médecine de Précision de Strasbourg, Transplantex NG, Faculté de Médecine, Fédération Hospitalo-Universitaire OMICARE, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, Strasbourg, France.,Unité de Recherche et d'Expertise Immunity and Inflammation, Institut Pasteur in New Caledonia, Pasteur Network, Nouméa, New Caledonia
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