Risk variants disrupting enhancers of TH1 and TREG cells in type 1 diabetes

Mesangial cell-derived CircRNAs in chronic glomerulonephritis: RNA sequencing and bioinformatics analysis

BACKGROUND

Circular RNAs (circRNAs) have been shown to play critical roles in the initiation and progression of chronic glomerulonephritis (CGN), while their role from mesangial cells in contributing to the pathogenesis of CGN is rarely understood. Our study aims to explore the potential functions of mesangial cell-derived circRNAs using RNA sequencing (RNA-seq) and bioinformatics analysis.

METHODS

Mouse mesangial cells (MMCs) were stimulated by lipopolysaccharide (LPS) to establish an in vitro model of CGN. Pro-inflammatory cytokines and cell cycle stages were detected by Enzyme-linked immunosorbent assay (ELISA) and Flow Cytometry experiment, respectively. Subsequently, differentially expressed circRNAs (DE-circRNAs) were identified by RNA-seq. GEO microarrays were used to identify differentially expressed mRNAs (DE-mRNAs) between CGN and healthy populations. Weighted co-expression network analysis (WGCNA) was utilized to explore clinically significant modules of CGN. CircRNA-associated CeRNA networks were constructed by bioinformatics analysis. The hub mRNAs from CeRNA network were identified using LASSO algorithms. Furthermore, utilizing protein-protein interaction (PPI), gene ontology (GO), pathway enrichment (KEGG), and GSEA analyses to explore the potential biological function of target genes from CeRNA network. In addition, we investigated the relationships between immune cells and hub mRNAs from CeRNA network using CIBERSORT.

RESULTS

The expression of pro-inflammatory cytokines IL-1β, IL-6, and TNF-α was drastically increased in LPS-induced MMCs. The number of cells decreased significantly in the G1 phase but increased significantly in the S/G2 phase. A total of 6 DE-mRNAs were determined by RNA-seq, including 4 up-regulated circRNAs and 2 down-regulated circRNAs. WGCNA analysis identified 1747 DE-mRNAs of the turquoise module from CGN people in the GEO database. Then, the CeRNA networks, including 6 circRNAs, 38 miRNAs, and 80 mRNAs, were successfully constructed. The results of GO and KEGG analyses revealed that the target mRNAs were mainly enriched in immune, infection, and inflammation-related pathways. Furthermore, three hub mRNAs (BOC, MLST8, and HMGCS2) from the CeRNA network were screened using LASSO algorithms. GSEA analysis revealed that hub mRNAs were implicated in a great deal of immune system responses and inflammatory pathways, including IL-5 production, MAPK signaling pathway, and JAK-STAT signaling pathway. Moreover, according to an evaluation of immune infiltration, hub mRNAs have statistical correlations with neutrophils, plasma cells, monocytes, and follicular helper T cells.

CONCLUSIONS

Our findings provide fundamental and novel insights for further investigations into the role of mesangial cell-derived circRNAs in CGN pathogenesis.

A great diversity of ROBO4 expression and regulations identified by data mining and transgene mice

ROBO4 involves in the stabilization of blood vessel and mediates the migration of hematopoietic stem cell and newborn neuron. However, the patterns of expression and regulation are not quite clear. To resolve this, we analyzed the single cell sequence data, and confirmed that Robo4 mainly expresses in various endothelial cells, but also in epithelial cells, pericytes, and stem or progenitor cells of bone marrow, fibroblast cells/mesenchymal stem cell of adipose tissues, muscle cells and neuron. Robo4 expressions in endothelial cells derived from capillary vessel, tip/stalk/activated endothelial cells were higher than that in artery and large vein (matured endothelial cells). On the other hand, via mining the gene expression data deposited in the NCBI Gene Expression Omnibus database as well as National Genomics Data Center (NGDC), we uncovered that the expression of Robo4 were regulated by different stimulus and variable in diseases' condition.Moreover, we constructed enhanced GFP (eGFP) transgene mouse controlled by Robo4 promoter using CRISPR/CAS9 system. We found GFP signals in many cell types from the embryonic section, confirming a widely expression of Robo4. Together, Robo4 widely and dynamically express in multiple cell types, and can be regulated by diverse factors.

An autoimmune transcriptional circuit drives FOXP3+ regulatory T cell dysfunction

Autoimmune diseases, among the most common disorders of young adults, are mediated by genetic and environmental factors. Although CD4+FOXP3+ regulatory T cells (Tregs) play a central role in preventing autoimmunity, the molecular mechanism underlying their dysfunction is unknown. Here, we performed comprehensive transcriptomic and epigenomic profiling of Tregs in the autoimmune disease multiple sclerosis (MS) to identify critical transcriptional programs regulating human autoimmunity. We found that up-regulation of a primate-specific short isoform of PR domain zinc finger protein 1 (PRDM1-S) induces expression of serum and glucocorticoid-regulated kinase 1 (SGK1) independent from the evolutionarily conserved long PRDM1, which led to destabilization of forkhead box P3 (FOXP3) and Treg dysfunction. This aberrant PRDM1-S/SGK1 axis is shared among other autoimmune diseases. Furthermore, the chromatin landscape profiling in Tregs from individuals with MS revealed enriched activating protein-1 (AP-1)/interferon regulatory factor (IRF) transcription factor binding as candidate upstream regulators of PRDM1-S expression and Treg dysfunction. Our study uncovers a mechanistic model where the evolutionary emergence of PRDM1-S and epigenetic priming of AP-1/IRF may be key drivers of dysfunctional Tregs in autoimmune diseases.

Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights

Understanding the influence of cis-regulatory elements on gene regulation poses numerous challenges given complexities stemming from variations in transcription factor (TF) binding, chromatin accessibility, structural constraints, and cell-type differences. This review discusses the role of gene regulatory networks in enhancing understanding of transcriptional regulation and covers construction methods ranging from expression-based approaches to supervised machine learning. Additionally, key experimental methods, including MPRAs and CRISPR-Cas9-based screening, which have significantly contributed to understanding TF binding preferences and cis-regulatory element functions, are explored. Lastly, the potential of machine learning and artificial intelligence to unravel cis-regulatory logic is analyzed. These computational advances have far-reaching implications for precision medicine, therapeutic target discovery, and the study of genetic variations in health and disease.

Knockout of Sema4D alleviates liver fibrosis by suppressing AOX1 expression

Liver fibrosis can occur in many chronic liver diseases, and no effective treatments are available due to the poorly characterized molecular pathogenesis. Semaphorin 4D (Sema4D) has immune functions and serves important roles in T cell priming. Here, we found that Sema4D was highly expressed in fibrotic liver, and the expression of Sema4D increased with hepatic stellate cells (HSCs) activation. Knockout of Sema4D alleviated liver fibrosis. Mechanistically, knockout of Sema4D alleviated liver fibrosis by suppressing the expression of AOX1 in retinol metabolism. Further investigation demonstrated that retinoic acid receptor α (RARA), an important nuclear receptor of retinoic acid, was reduced by Sema4D knockout during liver fibrogenesis. Sema4D knockout-mediated suppression of liver fibrosis was partly mediated by regulating the balance of Th1, Th2, Th17, and T-bet+Treg cells via inhibiting AOX1/RARA. Thus, targeting Sema4D may hold promise as a potential therapeutic approach for treating liver fibrosis.

Computational Assessment of the Expression-modulating Potential for Non-coding Variants

Large-scale genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) studies have identified multiple non-coding variants associated with genetic diseases by affecting gene expression. However, pinpointing causal variants effectively and efficiently remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional non-coding expression-modulating variants. Multiple evaluations demonstrated CARMEN's superior performance over state-of-the-art tools. Applying CARMEN to GWAS and eQTL datasets further pinpointed several causal variants other than the reported lead single-nucleotide polymorphisms (SNPs). CARMEN scales well with the massive datasets, and is available online as a web server at http://carmen.gao-lab.org.

Genomic Analysis of Foxp3 Function in Regulatory T Cells

Regulatory T (Treg) cells are critical for tolerance to self-antigens and for preventing autoimmunity. Foxp3 has been identified as a Treg cell lineage-defining transcription factor controlling Treg cell differentiation and function. In this article, we review the current mechanistic and systemic understanding of Foxp3 function enabled by experimental and computational advances in high-throughput genomics.

A novel diabetes typology: towards precision diabetology from pathogenesis to treatment

The current classification of diabetes, based on hyperglycaemia, islet-directed antibodies and some insufficiently defined clinical features, does not reflect differences in aetiological mechanisms and in the clinical course of people with diabetes. This review discusses evidence from recent studies addressing the complexity of diabetes by proposing novel subgroups (subtypes) of diabetes. The most widely replicated and validated approach identified, in addition to severe autoimmune diabetes, four subgroups designated severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes and mild age-related diabetes subgroups. These subgroups display distinct patterns of clinical features, disease progression and onset of comorbidities and complications, with severe insulin-resistant diabetes showing the highest risk for cardiovascular, kidney and fatty liver diseases. While it has been suggested that people in these subgroups would benefit from stratified treatments, RCTs are required to assess the clinical utility of any reclassification effort. Several methodological and practical issues also need further study: the statistical approach used to define subgroups and derive recommendations for diabetes care; the stability of subgroups over time; the optimal dataset (e.g. phenotypic vs genotypic) for reclassification; the transethnic generalisability of findings; and the applicability in clinical routine care. Despite these open questions, the concept of a new classification of diabetes has already allowed researchers to gain more insight into the colourful picture of diabetes and has stimulated progress in this field so that precision diabetology may become reality in the future.

Changes of macrophage and CD4+ T cell in inflammatory response in type 1 diabetic mice

Immune cells play an important role in the development of inflammation in type 1 diabetes mellitus, so we want to explore the changes of CD4+ T cells and macrophages in vivo, which can provide an experimental basis for immunotherapy based on CD4+ T cells and macrophages. The intraperitoneal injection of streptozocin was used to induce a type 1 diabetes mellitus mouse model; the blood glucose, body weight, and the expression of inflammatory factors in the kidney were measured. Immunohistochemistry was applied to determine and analyze the infiltration of CD4+ T cells and macrophages in the spleen, pancreas, and kidney. The subtypes of macrophages in the kidney and CD4+ T cells in the spleen were analyzed by flow cytometry. Our study suggests that CD4+ T cells and macrophages increase, while the inflammatory immune response system is activated in the development of T1DM. CD4+ T cells positively correlated with macrophages in the pancreas and kidney of T1DM. CD4+ T cells turn to pro-inflammatory subtypes in the spleen of T1DM, while macrophages turn to pro-inflammatory subtypes in the kidney of T1DM. Therefore, regulation of CD4+ T cells and macrophages may be a potential target for T1DM and kidney complications.

Rebooting Regulatory T Cell and Dendritic Cell Function in Immune-Mediated Inflammatory Diseases: Biomarker and Therapy Discovery under a Multi-Omics Lens

Immune-mediated inflammatory diseases (IMIDs) are a group of autoimmune and chronic inflammatory disorders with constantly increasing prevalence in the modern world. The vast majority of IMIDs develop as a consequence of complex mechanisms dependent on genetic, epigenetic, molecular, cellular, and environmental elements, that lead to defects in immune regulatory guardians of tolerance, such as dendritic (DCs) and regulatory T (Tregs) cells. As a result of this dysfunction, immune tolerance collapses and pathogenesis emerges. Deeper understanding of such disease driving mechanisms remains a major challenge for the prevention of inflammatory disorders. The recent renaissance in high throughput technologies has enabled the increase in the amount of data collected through multiple omics layers, while additionally narrowing the resolution down to the single cell level. In light of the aforementioned, this review focuses on DCs and Tregs and discusses how multi-omics approaches can be harnessed to create robust cell-based IMID biomarkers in hope of leading to more efficient and patient-tailored therapeutic interventions.

Nature vs. nurture: FOXP3, genetics, and tissue environment shape Treg function

The importance of regulatory T cells (Tregs) in preventing autoimmunity has been well established; however, the precise alterations in Treg function in autoimmune individuals and how underlying genetic associations impact the development and function of Tregs is still not well understood. Polygenetic susceptibly is a key driving factor in the development of autoimmunity, and many of the pathways implicated in genetic association studies point to a potential alteration or defect in regulatory T cell function. In this review transcriptomic control of Treg development and function is highlighted with a focus on how these pathways are altered during autoimmunity. In combination, observations from autoimmune mouse models and human patients now provide insights into epigenetic control of Treg function and stability. How tissue microenvironment influences Treg function, lineage stability, and functional plasticity is also explored. In conclusion, the current efficacy and future direction of Treg-based therapies for Type 1 Diabetes and other autoimmune diseases is discussed. In total, this review examines Treg function with focuses on genetic, epigenetic, and environmental mechanisms and how Treg functions are altered within the context of autoimmunity.

Pathogenesis of Type 1 Diabetes: Established Facts and New Insights

Type 1 diabetes (T1D) is an autoimmune disease characterized by the T-cell-mediated destruction of insulin-producing β-cells in pancreatic islets. It generally occurs in genetically susceptible individuals, and genetics plays a major role in the development of islet autoimmunity. Furthermore, these processes are heterogeneous among individuals; hence, different endotypes have been proposed. In this review, we highlight the interplay between genetic predisposition and other non-genetic factors, such as viral infections, diet, and gut biome, which all potentially contribute to the aetiology of T1D. We also discuss a possible active role for β-cells in initiating the pathological processes. Another component in T1D predisposition is epigenetic influences, which represent a link between genetic susceptibility and environmental factors and may account for some of the disease heterogeneity. Accordingly, a shift towards personalized therapies may improve the treatment results and, therefore, result in better outcomes for individuals in the long-run. There is also a clear need for a better understanding of the preclinical phases of T1D and finding new predictive biomarkers for earlier diagnosis and therapy, with the final goal of reverting or even preventing the development of the disease.

Variants on the UBE2L3/YDJC Autoimmune Disease Risk Haplotype Increase UBE2L3 Expression by Modulating CCCTC-Binding Factor and YY1 Binding

OBJECTIVE

Genetic variants spanning UBE2L3 are associated with increased expression of the UBE2L3-encoded E2 ubiquitin-conjugating enzyme H7 (UbcH7), which facilitates activation of proinflammatory NF-κB signaling and susceptibility to autoimmune diseases. We undertook this study to delineate how genetic variants carried on the UBE2L3/YDJC autoimmune risk haplotype function to drive hypermorphic UBE2L3 expression.

METHODS

We used bioinformatic analyses, electrophoretic mobility shift assays, and luciferase reporter assays to identify and functionally characterize allele-specific effects of risk variants positioned in chromatin accessible regions of immune cells. Chromatin conformation capture with quantitative polymerase chain reaction (3C-qPCR), chromatin immunoprecipitation (ChIP)-qPCR, and small interfering RNA (siRNA) knockdown assays were performed on patient-derived Epstein-Barr virus-transformed B cells homozygous for the UBE2L3/YDJC nonrisk or risk haplotype to determine if the risk haplotype increases UBE2L3 expression by altering the regulatory chromatin architecture in the region.

RESULTS

Of the 7 prioritized variants, 5 demonstrated allele-specific increases in nuclear protein binding affinity and regulatory activity. High-throughput sequencing of chromosome conformation capture coupled with ChIP (HiChIP) and 3C-qPCR uncovered a long-range interaction between the UBE2L3 promoter (rs140490, rs140491, rs11089620) and the downstream YDJC promoter (rs3747093) that was strengthened in the presence of the UBE2L3/YDJC risk haplotype, and correlated with the loss of CCCTC-binding factor (CTCF) and gain of YY1 binding at the risk alleles. Depleting YY1 by siRNA disrupted the long-range interaction between the 2 promoters and reduced UBE2L3 expression.

CONCLUSION

The UBE2L3/YDJC autoimmune risk haplotype increases UBE2L3 expression through strengthening a YY1-mediated interaction between the UBE2L3 and YDJC promoters.

Emerging Concepts in Immune Thrombotic Thrombocytopenic Purpura

Immune thrombotic thrombocytopenic purpura (iTTP) is an autoimmune disorder of which the etiology is not fully understood. Autoantibodies targeting ADAMTS13 in iTTP patients have extensively been studied, the immunological mechanisms leading to the breach of tolerance remain to be uncovered. This review addresses the current knowledge on genetic factors associated with the development of iTTP and the interplay between the patient's immune system and environmental factors in the induction of autoimmunity against ADAMTS13. HLA-DRB1*11 has been identified as a risk factor for iTTP in the Caucasian population. Interestingly, HLA-DRB1*08:03 was recently identified as a risk factor in the Japanese population. Combined in vitro and in silico MHC class II peptide presentation approaches suggest that an ADAMTS13-derived peptide may bind to both HLA-DRB1*11 and HLA-DRB1*08:03 through different anchor-residues. It is apparent that iTTP is associated with the presence of infectious microorganisms, viruses being the most widely associated with development of iTTP. Infections may potentially lead to loss of tolerance resulting in the shift from immune homeostasis to autoimmunity. In the model we propose in this review, infections disrupt the epithelial barriers in the gut or lung, promoting exposure of antigen presenting cells in the mucosa-associated lymphoid tissue to the microorganisms. This may result in breach of tolerance through the presentation of microorganism-derived peptides that are homologous to ADAMTS13 on risk alleles for iTTP.

A comprehensive integrated post-GWAS analysis of Type 1 diabetes reveals enhancer-based immune dysregulation

Type 1 diabetes (T1D) is an organ-specific autoimmune disease, whereby immune cell-mediated killing leads to loss of the insulin-producing β cells in the pancreas. Genome-wide association studies (GWAS) have identified over 200 genetic variants associated with risk for T1D. The majority of the GWAS risk variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes substantially contribute to T1D. However, identification of causal regulatory variants associated with T1D risk and their affected genes is challenging due to incomplete knowledge of non-coding regulatory elements and the cellular states and processes in which they function. Here, we performed a comprehensive integrated post-GWAS analysis of T1D to identify functional regulatory variants in enhancers and their cognate target genes. Starting with 1,817 candidate T1D SNPs defined from the GWAS catalog and LDlink databases, we conducted functional annotation analysis using genomic data from various public databases. These include 1) Roadmap Epigenomics, ENCODE, and RegulomeDB for epigenome data; 2) GTEx for tissue-specific gene expression and expression quantitative trait loci data; and 3) lncRNASNP2 for long non-coding RNA data. Our results indicated a prevalent enhancer-based immune dysregulation in T1D pathogenesis. We identified 26 high-probability causal enhancer SNPs associated with T1D, and 64 predicted target genes. The majority of the target genes play major roles in antigen presentation and immune response and are regulated through complex transcriptional regulatory circuits, including those in HLA (6p21) and non-HLA (16p11.2) loci. These candidate causal enhancer SNPs are supported by strong evidence and warrant functional follow-up studies.

An engineered probiotic secreting Sj16 ameliorates colitis via Ruminococcaceae/butyrate/retinoic acid axis

Most inflammatory bowel disease (IBD) patients are unable to maintain a lifelong remission. Developing a novel therapeutic strategy is urgently needed. In this study, we adopt a new strategy to attenuate colitis using the Escherichia coli Nissle 1917 probiotic strain to express a schistosome immunoregulatory protein (Sj16) in the gastrointestinal tract. The genetically engineered Nissle 1917 (EcN-Sj16) highly expressed Sj16 in the gastrointestinal tracts of dextran sulfate sodium-induced colitis mice and significantly attenuated the clinical activity of colitis mice. Mechanistically, EcN-Sj16 increased the intestinal microbiota diversity and selectively promoted the growth of Ruminococcaceae and therefore enhanced the butyrate production. Butyrate induced the expression of retinoic acid, which further attenuated the clinical activity of colitis mice by increasing Treg cells and decreasing Th17. Strikingly, retinoic acid inhibitor inhibited the therapeutic effects of EcN-Sj16 in colitis mice. These findings suggest that EcN-Sj16 represents a novel engineered probiotic that may be used to treat IBD.

Conserved human effector Treg cell transcriptomic and epigenetic signature in arthritic joint inflammation

Treg cells are critical regulators of immune homeostasis, and environment-driven Treg cell differentiation into effector (e)Treg cells is crucial for optimal functioning. However, human Treg cell programming in inflammation is unclear. Here, we combine transcriptional and epigenetic profiling to identify a human eTreg cell signature. Inflammation-derived functional Treg cells have a transcriptional profile characterized by upregulation of both a core Treg cell (FOXP3, CTLA4, TIGIT) and effector program (GITR, BLIMP-1, BATF). We identify a specific human eTreg cell signature that includes the vitamin D receptor (VDR) as a predicted regulator in eTreg cell differentiation. H3K27ac/H3K4me1 occupancy indicates an altered (super-)enhancer landscape, including enrichment of the VDR and BATF binding motifs. The Treg cell profile has striking overlap with tumor-infiltrating Treg cells. Our data demonstrate that human inflammation-derived Treg cells acquire a conserved and specific eTreg cell profile guided by epigenetic changes, and fine-tuned by environment-specific adaptations.

Integrative Bulk and Single-Cell Profiling of Premanufacture T-cell Populations Reveals Factors Mediating Long-Term Persistence of CAR T-cell Therapy

The adoptive transfer of chimeric antigen receptor (CAR) T cells represents a breakthrough in clinical oncology, yet both between- and within-patient differences in autologously derived T cells are a major contributor to therapy failure. To interrogate the molecular determinants of clinical CAR T-cell persistence, we extensively characterized the premanufacture T cells of 71 patients with B-cell malignancies on trial to receive anti-CD19 CAR T-cell therapy. We performed RNA-sequencing analysis on sorted T-cell subsets from all 71 patients, followed by paired Cellular Indexing of Transcriptomes and Epitopes (CITE) sequencing and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) on T cells from six of these patients. We found that chronic IFN signaling regulated by IRF7 was associated with poor CAR T-cell persistence across T-cell subsets, and that the TCF7 regulon not only associates with the favorable naïve T-cell state, but is maintained in effector T cells among patients with long-term CAR T-cell persistence. These findings provide key insights into the underlying molecular determinants of clinical CAR T-cell function. SIGNIFICANCE: To improve clinical outcomes for CAR T-cell therapy, there is a need to understand the molecular determinants of CAR T-cell persistence. These data represent the largest clinically annotated molecular atlas in CAR T-cell therapy to date, and significantly advance our understanding of the mechanisms underlying therapeutic efficacy.This article is highlighted in the In This Issue feature, p. 2113.

A catalog of GWAS fine-mapping efforts in autoimmune disease

Genome-wide association studies (GWASs) have enabled unbiased identification of genetic loci contributing to common complex diseases. Because GWAS loci often harbor many variants and genes, it remains a major challenge to move from GWASs’ statistical associations to the identification of causal variants and genes that underlie these association signals. Researchers have applied many statistical and functional fine-mapping strategies to prioritize genetic variants and genes as potential candidates. There is no gold standard in fine-mapping approaches, but consistent results across different approaches can improve confidence in the fine-mapping findings. Here, we combined text mining with a systematic review and formed a catalog of 85 studies with evidence of fine mapping for at least one autoimmune GWAS locus. Across all fine-mapping studies, we compiled 230 GWAS loci with allelic heterogeneity estimates and predictions of causal variants and trait-relevant genes. These 230 loci included 455 combinations of locus-by-disease association signals with 15 autoimmune diseases. Using these estimates, we assessed the probability of mediating disease risk associations across genes in GWAS loci and identified robust signals of causal disease biology. We predict that this comprehensive catalog of GWAS fine-mapping efforts in autoimmune disease will greatly help distill the plethora of information in the field and inform therapeutic strategies.

Functional genomics in autoimmune diseases

Associations between genetic loci and increased susceptibility to autoimmune disease have been well characterized, however, translating this knowledge into mechanistic insight and patient benefit remains a challenge. While improvements in the precision, completeness and accuracy of our genetic understanding of autoimmune diseases will undoubtedly be helpful, meeting this challenge will require two interlinked problems to be addressed: first which of the highly correlated variants at an individual locus is responsible for increased disease risk, and second what are the downstream effects of this variant. Given that the majority of loci are thought to affect non-coding regulatory elements, the second question is often reframed as what are the target gene(s) and pathways affected by causal variants. Currently, these questions are being addressed using a wide variety of novel techniques and datasets. In many cases, these approaches are complementary and it is likely that the most accurate picture will be generated by consolidating information relating to transcription, regulatory activity, chromatin accessibility, chromatin conformation and readouts from functional experiments, such as genome editing and reporter assays. It is clear that it will be necessary to gather this information from disease relevant cell types and conditions and that by doing so our understanding of disease etiology will be improved. This review is focused on the field of autoimmune disease functional genomics with a particular focus on the most exciting and significant research to be published within the last couple of years.

Influence of single gene variants of FOXP3 on allergic asthma predisposition

BACKGROUND

The role of FoxP3, a master regulator of T regulatory cells, in allergic diseases such as asthma is of immense importance yet the effect of its gene variants on the disease predisposition is not fully understood. We studied the association of FoxP3 polymorphisms (-2383C/T and -3279C/A) in allergic asthma patients and their correlation with serum IL-4, IL-13, Total IgE, and Vitamin D levels.

METHODS

In this study 350 individuals were enrolled, 150 allergic asthma patients and 200 healthy controls. SNP analyses were performed by RFLP. IL-4, IL-13 vitamin D and Total IgE were measured by ELISA.

RESULTS

The AA homozygous mutant of -3279C/A posed a three-fold risk [P < 0.005; OR, 3.52] whereas the -2383C/T variants TT genotype carried a fourfold risk [P = 0.002; OR, 4.04]. Haplotype analysis exhibited predisposition to allergic asthmawith CC/TT [P = 0.01; OR 5.93 (95%CI)], AA/CC [P = 0.01; OR 3.29] and AA/TT haplotypes [P = 0; OR 11.86 (1.31-85.87)]. A negative correlation between IgE and Vitamin D was found [r = -0.30p-value 0.001] but a negative correlation betweenIgE and Vit D was established in the haplotype CC/TT [r = -0.45P = 0.002] and CC/CT [r = -0.52P = 0.04]. In allergic patients, the eosinophils count was high [p = 0.003] and the mean levels of pro-inflammatory cytokines IL-4 and IL-13 were elevated [P < 0.001] as well.

CONCLUSIONS

The study suggests SNP -3279 -AA genotype and, -2383-TT genotype in association with certain haplotypes pose a risk for allergy development. There was no correlation between different genotypes and serum levels of various cytokines.

Regulation of inflammation in diabetes: From genetics to epigenomics evidence

Background

Diabetes is one of the greatest public health challenges worldwide, and we still lack complementary approaches to significantly enhance the efficacy of preventive and therapeutic approaches. Genetic and environmental factors are the culprits involved in diabetes risk. Evidence from the last decade has highlighted that deregulation in the immune and inflammatory responses increase susceptibility to type 1 and type 2 diabetes. Spatiotemporal patterns of gene expression involved in immune cell polarisation depend on genomic enhancer elements in response to inflammatory and metabolic cues. Several studies have reported that most regulatory genetic variants are located in the non-protein coding regions of the genome and particularly in enhancer regions. The progress of high-throughput technologies has permitted the characterisation of enhancer chromatin properties. These advances support the concept that genetic alteration of enhancers may influence the immune and inflammatory responses in relation to diabetes.

Scope of review

Results from genome-wide association studies (GWAS) combined with functional and integrative analyses have elucidated the impacts of some diabetes risk-associated variants that are involved in the regulation of the immune system. Additionally, genetic variant mapping to enhancer regions may alter enhancer status, which in turn leads to aberrant expression of inflammatory genes associated with diabetes susceptibility. The focus of this review was to provide an overview of the current indications that inflammatory processes are regulated at the genetic and epigenomic levels in diabetes, along with perspectives on future research avenues that may improve understanding of the disease.

Major conclusions

In this review, we provide genetic evidence in support of a deregulated immune response as a risk factor in diabetes. We also argue about the importance of enhancer regions in the regulation of immune cell polarisation and how the recent advances using genome-wide methods for enhancer identification have enabled the determination of the impact of enhancer genetic variation on diabetes onset and phenotype. This could eventually lead to better management plans and improved treatment responses in human diabetes.

Transcriptional regulatory network controlling the ontogeny of hematopoietic stem cells

In this study from Gao et al., the authors performed RNA-seq and histone mark ChIP-seq to define the transcriptomes and epigenomes of cells representing key developmental stages of HSC ontogeny in mice. Using a novel computational algorithm, target inference via physical connection (TIPC), they constructed developmental stage-specific transcriptional regulatory networks by linking enhancers and predicted bound transcription factors to their target promoters, thus providing a useful resource for uncovering regulators of HSC formation.

Hematopoietic stem cell (HSC) ontogeny is accompanied by dynamic changes in gene regulatory networks. We performed RNA-seq and histone mark ChIP-seq to define the transcriptomes and epigenomes of cells representing key developmental stages of HSC ontogeny in mice. The five populations analyzed were embryonic day 10.5 (E10.5) endothelium and hemogenic endothelium from the major arteries, an enriched population of prehematopoietic stem cells (pre-HSCs), fetal liver HSCs, and adult bone marrow HSCs. Using epigenetic signatures, we identified enhancers for each developmental stage. Only 12% of enhancers are primed, and 78% are active, suggesting the vast majority of enhancers are established de novo without prior priming in earlier stages. We constructed developmental stage-specific transcriptional regulatory networks by linking enhancers and predicted bound transcription factors to their target promoters using a novel computational algorithm, target inference via physical connection (TIPC). TIPC predicted known transcriptional regulators for the endothelial-to-hematopoietic transition, validating our overall approach, and identified putative novel transcription factors, including the broadly expressed transcription factors SP3 and MAZ. Finally, we validated a role for SP3 and MAZ in the formation of hemogenic endothelium. Our data and computational analyses provide a useful resource for uncovering regulators of HSC formation.

The Genetic Contribution to Type 1 Diabetes

PURPOSE OF REVIEW

To provide an updated summary of discoveries made to date resulting from genome-wide association study (GWAS) and sequencing studies, and to discuss the latest loci added to the growing repertoire of genetic signals predisposing to type 1 diabetes (T1D).

RECENT FINDINGS

Genetic studies have identified over 60 loci associated with T1D susceptibility. GWAS alone does not specifically inform on underlying mechanisms, but in combination with other sequencing and omics-data, advances are being made in our understanding of T1D genetic etiology and pathogenesis. Current knowledge indicates that genetic variation operating in both pancreatic β cells and in immune cells is central in mediating T1D risk. One of the main challenges is to determine how these recently discovered GWAS-implicated variants affect the expression and function of gene products. Once we understand the mechanism of action for disease-causing variants, we will be well placed to apply targeted genomic approaches to impede the premature activation of the immune system in an effort to ultimately prevent the onset of T1D.

Advances in Research on Diabetes by Human Nutriomics

The incidence and prevalence of diabetes mellitus (DM) have increased rapidly worldwide over the last two decades. Because the pathogenic factors of DM are heterogeneous, determining clinically effective treatments for DM patients is difficult. Applying various nutrient analyses has yielded new insight and potential treatments for DM patients. In this review, we summarized the omics analysis methods, including nutrigenomics, nutritional-metabolomics, and foodomics. The list of the new targets of SNPs, genes, proteins, and gut microbiota associated with DM has been obtained by the analysis of nutrigenomics and microbiomics within last few years, which provides a reference for the diagnosis of DM. The use of nutrient metabolomics analysis can obtain new targets of amino acids, lipids, and metal elements, which provides a reference for the treatment of DM. Foodomics analysis can provide targeted dietary strategies for DM patients. This review summarizes the DM-associated molecular biomarkers in current applied omics analyses and may provide guidance for diagnosing and treating DM.