Cell lineage-specific methylome and genome alterations in gout

The causal association between immune cells and gout: A bidirectional two-sample Mendelian randomization study

Gout, a metabolic disorder, is increasingly being linked to immune cells. However, the causal relationships between these factors remain unclear. Our study aimed to elucidate the causal relationship between immune cells and gout. Our study used 2-sample Mendelian randomization (MR) to explore the causal relationship between immune cells and gout. It is noteworthy that we utilized 5 methods MR-Egger, weighted median, inverse variance weighted, weighted mode, and simple mode to ensure the reliability of the results. Comprehensive sensitivity analyses were performed to verify the robustness, heterogeneity, and horizontal pleiotropy of the results. After false discovery rate correction (PFDR <0.20), 3 immunophenotypes were identified: one in the B cell panel, one in the regulatory T cells panel, and another in the T lymphocytes, B lymphocytes, Natural Killer cells panel. Among them, 2 immunophenotypes (CD4-CD8-T cell absolute count and CD25 on IgD + CD24 + B cell) increased the risk of developing gout, whereas the other one immunophenotype (CD45RA + CD28- CD8 + T cell %T cell) decreased the risk of gout. Subsequently, we did not observe heterogeneity and horizontal pleiotropy stable in these data through comprehensive sensitivity analyses. Furthermore, we identified some positive results in reverse MR analysis, but after false discovery rate correction (PFDR <0.20), no significant results were detected. Our study revealed causal relationships between immune cells and gout, providing novel insights into the prevention and treatment of gout.

Genetic and epigenetic dysregulation of innate immune mechanisms in autoinflammatory diseases

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.

The pathogenesis of gout: molecular insights from genetic, epigenomic and transcriptomic studies

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.

Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts

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.

Genetic and Epigenetic Regulation of the Innate Immune Response to Gout

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.

Association between night shift work and methylation of a subset of immune-related genes

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.

Mitochondrial VDAC1: A Potential Therapeutic Target of Inflammation-Related Diseases and Clinical Opportunities

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.

MiR-196a promotes the proliferation and migration of esophageal cancer via the UHRF2/TET2 axis

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.

Where Epigenetics Meets Food Intake: Their Interaction in the Development/Severity of Gout and Therapeutic Perspectives

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.