Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

Islet cells in human type 1 diabetes: from recent advances to novel therapies - a symposium-based roadmap for future research

There is a growing understanding that the early phases of type 1 diabetes (T1D) are characterised by a deleterious dialogue between the pancreatic beta cells and the immune system. This, combined with the urgent need to better translate this growing knowledge into novel therapies, provided the background for the JDRF-DiabetesUK-INNODIA-nPOD symposium entitled 'Islet cells in human T1D: from recent advances to novel therapies', which took place in Stockholm, Sweden, in September 2022. We provide in this article an overview of the main themes addressed in the symposium, pointing to both promising conclusions and key unmet needs that remain to be addressed in order to achieve better approaches to prevent or reverse T1D.

Type 1 diabetes

Type 1 diabetes is a chronic disease caused by autoimmune destruction of pancreatic β cells. Individuals with type 1 diabetes are reliant on insulin for survival. Despite enhanced knowledge related to the pathophysiology of the disease, including interactions between genetic, immune, and environmental contributions, and major strides in treatment and management, disease burden remains high. Studies aimed at blocking the immune attack on β cells in people at risk or individuals with very early onset type 1 diabetes show promise in preserving endogenous insulin production. This Seminar will review the field of type 1 diabetes, highlighting recent progress within the past 5 years, challenges to clinical care, and future directions in research, including strategies to prevent, manage, and cure the disease.

Cathepsin H: molecular characteristics and clues to function and mechanism

Cathepsin H (CatH) is a lysosomal cysteine protease with a unique aminopeptidase activity that is extensively expressed in the lung, pancreas, thymus, kidney, liver, skin, and brain. Owing to its specific enzymatic activity, CatH has critical effects on the regulation of biological behaviours of cancer cells and pathological processes in brain diseases. Moreover, a neutral pH level is optimal for CatH activity, so it is expected to be active in the extra-lysosomal and extracellular space. In the present review, we describe the expression, maturation, and enzymatic properties of CatH, and summarize the available experimental evidence that mechanistically links CatH to various physiological and pathological processes. Finally, we discuss the challenges and potentials of CatH inhibitors in CatH-induced disease therapy.

Inflammatory Cytokines Rewire the Proinsulin Interaction Network in Human Islets

CONTEXT

Aberrant biosynthesis and secretion of the insulin precursor proinsulin occurs in both type I and type II diabetes. Inflammatory cytokines are implicated in pancreatic islet stress and dysfunction in both forms of diabetes, but the mechanisms remain unclear.

OBJECTIVE

We sought to determine the effect of the diabetes-associated cytokines on proinsulin folding, trafficking, secretion, and β-cell function.

METHODS

Human islets were treated with interleukin-1β and interferon-γ for 48 hours, followed by analysis of interleukin-6, nitrite, proinsulin and insulin release, RNA sequencing, and unbiased profiling of the proinsulin interactome by affinity purification-mass spectrometry.

RESULTS

Cytokine treatment induced secretion of interleukin-6, nitrites, and insulin, as well as aberrant release of proinsulin. RNA sequencing showed that cytokines upregulated genes involved in endoplasmic reticulum stress, and, consistent with this, affinity purification-mass spectrometry revealed cytokine induced proinsulin binding to multiple endoplasmic reticulum chaperones and oxidoreductases. Moreover, increased binding to the chaperone immunoglobulin binding protein was required to maintain proper proinsulin folding in the inflammatory environment. Cytokines also regulated novel interactions between proinsulin and type 1 and type 2 diabetes genome-wide association studies candidate proteins not previously known to interact with proinsulin (eg, Ataxin-2). Finally, cytokines induced proinsulin interactions with a cluster of microtubule motor proteins and chemical destabilization of microtubules with Nocodazole exacerbated cytokine induced proinsulin secretion.

CONCLUSION

Together, the data shed new light on mechanisms by which diabetes-associated cytokines dysregulate β-cell function. For the first time, we show that even short-term exposure to an inflammatory environment reshapes proinsulin interactions with critical chaperones and regulators of the secretory pathway.

Ubiquitin-proteasome system in diabetic retinopathy

Diabetic retinopathy (DR) is the most common complication of diabetes, being the most prevalent reason for blindness among the working-age population in the developed world. Despite constant improvement of understanding of the pathogenesis of DR, identification of novel biomarkers of DR is needed for improvement of patient risk stratification and development of novel prevention and therapeutic approaches. The ubiquitin-proteasome system (UPS) is the primary protein quality control system responsible for recognizing and degrading of damaged proteins. This review aims to summarize literature data on modifications of UPS in diabetes and DR. First, we briefly review the structure and functions of UPS in physiological conditions. We then describe how UPS is involved in the development and progression of diabetes and touch upon the association of UPS genetic factors with diabetes and its complications. Further, we focused on the effect of diabetes-induced hyperglycemia, oxidative stress and hypoxia on UPS functioning, with examples of studies on DR. In other sections, we discussed the association of several other mechanisms of DR (endoplasmic reticulum stress, neurodegeneration etc) with UPS modifications. Finally, UPS-affecting drugs and remedies are reviewed. This review highlights UPS as a promising target for the development of therapies for DR prevention and treatment and identifies gaps in existing knowledge and possible future study directions.

Genome-wide Meta-analysis Reveals New Gene Signatures and Potential Drug Targets of Hypertension

The prevalence of hypertension reported around the world is increasing and is an important public health challenge. This study was designed to explore the disease's genetic variations and to identify new hypertension-related genes and target proteins. We analyzed 22 publicly available Affymetrix cDNA datasets of hypertension using an integrated system-level framework involving differential expression genetic (DEG) analysis, data mining, gene enrichment, protein-protein interaction, microRNA analysis, toxicogenomics, gene regulation, molecular docking, and simulation studies. We found potential DEGs after screening out the extracellular proteins. We studied the functional role of seven shortlisted DEGs (ADM, EDN1, ANGPTL4, NFIL3, MSR1, CEBPD, and USP8) in hypertension after disease gene curation analysis. The expression profiling and cluster analysis showed significant variations and enriched GO terms. hsa-miR-365a-3p, hsa-miR-2052, hsa-miR-3065-3p, hsa-miR-603, hsa-miR-7113-3p, hsa-miR-3923, and hsa-miR-524-5p were identified as hypertension-associated miRNA targets for each gene using computational algorithms. We found functional interactions of source DEGs with target and important gene signatures including EGFR, AGT, AVP, APOE, RHOA, SRC, APOB, STAT3, UBC, LPL, APOA1, and AKT1 associated with the disease. These DEGs are mainly involved in fatty acid metabolism, myometrial pathways, MAPK, and G-alpha signaling pathways linked with hypertension pathogenesis. We predicted significantly disordered regions of 71.2, 48.8, and 45.4% representing the mutation in the sequence of NFIL3, USP8, and ADM, respectively. Regulation of gene expression was performed to find upregulated genes. Molecular docking analysis was used to evaluate Food and Drug Administration-approved medicines against the four DEGs that were overexpressed. For each elevated target protein, the three best drug candidates were chosen. Furthermore, molecular dynamics (MD) simulation using the target's active sites for 100 ns was used to validate these 12 complexes after docking. This investigation establishes the worth of systems genetics for finding four possible genes as potential drug targets for hypertension. These network-based approaches are significant for finding genetic variant data, which will advance the understanding of how to hasten the identification of drug targets and improve the understanding regarding the treatment of hypertension.

HLA-DRB1 and -DQB1 Alleles, Haplotypes and Genotypes in Emirati Patients with Type 1 Diabetes Underscores the Benefits of Evaluating Understudied Populations

Background: HLA class II (DR and DQ) alleles and antigens have historically shown strong genetic predisposition to type 1 diabetes (T1D). This study evaluated the association of DRB1 and DQB1 alleles, genotypes, and haplotypes with T1D in United Arab Emirates. Materials and Methods: Study subjects comprised 149 patients with T1D, and 147 normoglycemic control subjects. Cases and controls were Emiratis and were HLA-DRB1 and -DQB1 genotyped using sequence-based typing. Statistical analysis was performed using Bridging Immunogenomic Data-Analysis Workflow Gaps R package. Results: In total, 15 DRB1 and 9 DQB1 alleles were identified in the study subjects, of which the association of DRB1*03:01, DRB1*04:02, DRB1*11:01, DRB1*16:02, and DQB1*02:01, DQB1*03:02, DQB1*03:01, and DQB1*06:01 with altered risk of T1D persisted after correcting for multiple comparisons. Two-locus haplotype analysis identified DRB1*03:01∼DQB1*02:01 [0.44 vs. 0.18, OR (95% CI) = 3.44 (2.33-5.1), Pc = 3.48 × 10^-10]; DRB1*04:02∼DQB1*03:02 [0.077 vs. 0.014, OR = 6.06 (2.03-24.37), Pc = 2.3 × 10^-3] and DRB1*04:05∼DQB1*03:02 [0.060 vs. 0.010, OR = 6.24 (1.79-33.34), Pc = 0.011] as positively associated, and DRB1*16:02∼DQB1*05:02 [0.024 vs. 0.075, OR = 0.3 (0.11-0.74), Pc = 0.041] as negatively associated with T1D, after applying Bonferroni correction. Furthermore, the highest T1D risk was observed for DR3/DR4 [0.104 vs. 0.006, OR = 25.03 (8.23-97.2), Pc = 2.6 × 10^-10], followed by DR3/DR3 [0.094 vs. 0.010, OR = 8.72 (3.17-25.32), Pc = 3.18 × 10^-8] diplotypes. Conclusion: While DRB1 and DQB1 alleles and haplotypes associated with T1D in Emiratis showed similarities to Caucasian and non-Caucasian populations, several alleles and haplotypes associated with T1D in European, African, and Asian populations, were not observed. This underscores the contribution of ethnic diversity and possible diverse associations between DRB1 and DQB1 and T1D across different populations.

OUP accepted manuscript

Although genome profiling provides important genetic and phenotypic details for applying precision medicine to diabetes, it is imperative to integrate in vitro human cell models, accurately recapitulating the genetic alterations associated with diabetes. The absence of the appropriate preclinical human models and the unavailability of genetically relevant cells substantially limit the progress in developing personalized treatment for diabetes. Human pluripotent stem cells (hPSCs) provide a scalable source for generating diabetes-relevant cells carrying the genetic signatures of the patients. Remarkably, allogenic hPSC-derived pancreatic progenitors and β cells are being used in clinical trials with promising preliminary results. Autologous hiPSC therapy options exist for those with monogenic and type 2 diabetes; however, encapsulation or immunosuppression must be accompanied with in the case of type 1 diabetes. Furthermore, genome-wide association studies-identified candidate variants can be introduced in hPSCs for deciphering the associated molecular defects. The hPSC-based disease models serve as excellent resources for drug development facilitating personalized treatment. Indeed, hPSC-based diabetes models have successfully provided valuable knowledge by modeling different types of diabetes, which are discussed in this review. Herein, we also evaluate their strengths and shortcomings in dissecting the underlying pathogenic molecular mechanisms and discuss strategies for improving hPSC-based disease modeling investigations.

The rs2304256 Polymorphism in TYK2 Gene Is Associated with Protection for Type 1 Diabetes Mellitus

BACKGROUND

Tyrosine kinase 2 (TYK2) is a candidate gene for type 1 diabetes mellitus (T1DM) since it plays an important role in regulating apoptotic and pro-inflammatory pathways in pancreatic β-cells through modulation of the type I interferon signaling pathway. The rs2304256 single nucleotide polymorphism (SNP) in TYK2 gene has been associated with protection for different autoimmune diseases. However, to date, only two studies have evaluated the association between this SNP and T1DM, with discordant results. This study thus aimed to investigate the association between the TYK2 rs2304256 SNP and T1DM in a Southern Brazilian population.

METHODS

This case-control study comprised 478 patients with T1DM and 518 non-diabetic subjects. The rs2304256 (C/A) SNP was genotyped by real-time polymerase chain reaction technique using TaqMan minor groove binder (MGB) probes.

RESULTS

Genotype and allele frequencies of the rs2304256 SNP differed between T1DM patients and non-diabetic subjects (P<0.0001 and P=0.001, respectively). Furthermore, the A allele was associated with protection against T1DM under recessive (odds ratio [OR], 0.482; 95% confidence interval [CI], 0.288 to 0.806) and additive (OR, 0.470; 95% CI, 0.278 to 0.794) inheritance models, adjusting for human leukocyte antigen (HLA) DR/DQ genotypes, gender, and ethnicity.

CONCLUSION

The A/A genotype of TYK2 rs2304256 SNP is associated with protection against T1DM in a Southern Brazilian population.

Elucidate multidimensionality of type 1 diabetes mellitus heterogeneity by multifaceted information

Type 1 diabetes (T1D) is an autoimmune disease. Different factors, including genetics and viruses may contribute to T1D, but the causes of T1D are not fully known, and there is currently no cure. The advent of high-throughput technologies has revolutionized the field of medicine and biology, and analysis of multi-source data along with clinical information has brought a better understanding of the mechanisms behind disease pathogenesis. The aim of this work was the development of a data repository linking clinical information and interactome studies in T1D. To address this goal, we analyzed the electronic health records and online databases of genes, proteins, miRNAs, and pathways to have a global view of T1D. There were common comorbid diseases such as anemia, hypertension, vitreous diseases, renal diseases, and atherosclerosis in the phenotypic disease networks. In the protein-protein interaction network, CASP3 and TNF were date-hub proteins involved in several pathways. Moreover, CTNNB1, IGF1R, and STAT3 were hub proteins, whereas miR-155-5p, miR-34a-5p, miR-23-3p, and miR-20a-5p were hub miRNAs in the gene-miRNA interaction network. Multiple levels of information including genetic, protein, miRNA and clinical data resulted in multiple results, which suggests the complementarity of multiple sources. With the integration of multifaceted information, it will shed light on the mechanisms underlying T1D; the provided data and repository has utility in understanding phenotypic disease networks for the potential development of comorbidities in T1D patients as well as the clues for further research on T1D comorbidities.

Self-Renewing Islet TCF1+ CD8 T Cells Undergo IL-27-Controlled Differentiation to Become TCF1- Terminal Effectors during the Progression of Type 1 Diabetes

In type 1 diabetes (T1D) autoreactive CD8 T cells infiltrate pancreatic islets and destroy insulin-producing β cells. Progression to T1D onset is a chronic process, which suggests that the effector activity of β-cell autoreactive CD8 T cells needs to be maintained throughout the course of disease development. The mechanism that sustains diabetogenic CD8 T cell effectors during the course of T1D progression has not been completely defined. Here we used single-cell RNA sequencing to gain further insight into the phenotypic complexity of islet-infiltrating CD8 T cells in NOD mice. We identified two functionally distinct subsets of activated CD8 T cells, CD44^highTCF1⁺CXCR6^- and CD44^highTCF1^-CXCR6⁺, in islets of prediabetic NOD mice. Compared with CD44^highTCF1⁺CXCR6^- CD8 T cells, the CD44^highTCF1^-CXCR6⁺ subset expressed higher levels of inhibitory and cytotoxic molecules and was more prone to apoptosis. Adoptive cell transfer experiments revealed that CD44^highTCF1⁺CXCR6^- CD8 T cells, through continuous generation of the CD44^highTCF1^-CXCR6⁺ subset, were more capable than the latter population to promote insulitis and the development of T1D. We further showed that direct IL-27 signaling in CD8 T cells promoted the generation of terminal effectors from the CD44^highTCF1⁺CXCR6^- population. These results indicate that islet CD44^highTCF1⁺CXCR6^- CD8 T cells are a progenitor-like subset with self-renewing capacity, and, under an IL-27-controlled mechanism, they differentiate into the CD44^highTCF1^-CXCR6⁺ terminal effector population. Our study provides new insight into the sustainability of the CD8 T cell response in the pathogenesis of T1D.

The role of PLCγ2 in immunological disorders, cancer, and neurodegeneration

Phosphatidylinositol-specific phospholipase Cγ2 (PLCγ2) is a critical signaling molecule activated downstream from a variety of cell surface receptors that contain an intracellular immunoreceptor tyrosine-based activation motif. These receptors recruit kinases such as Syk, BTK, and BLNK to phosphorylate and activate PLCγ2, which then generates 1D-myo-inositol 1,4,5-trisphosphate and diacylglycerol. These well-known second messengers are required for diverse membrane functionality including cellular proliferation, endocytosis, and calcium flux. As a result, PLCγ2 dysfunction is associated with a variety of diseases including cancer, neurodegeneration, and immune disorders. The diverse pathologies associated with PLCγ2 are exemplified by distinct genetic variants. Inherited mutations at this locus cause PLCγ2-associated antibody deficiency and immune dysregulation, in some cases with autoinflammation. Acquired mutations at this locus, which often arise as a result of BTK inhibition to treat chronic lymphocytic leukemia, result in constitutive downstream signaling and lymphocyte proliferation. Finally, a third group of PLCγ2 variants actually has a protective effect in a variety of neurodegenerative disorders, presumably by increased uptake and degradation of deleterious neurological aggregates. Therefore, manipulating PLCγ2 activity either up or down could have therapeutic benefit; however, we require a better understanding of the signaling pathways propagated by these variants before such clinical utility can be realized. Here, we review the signaling roles of PLCγ2 in hematopoietic cells to help understand the effect of mutations driving immune disorders and cancer and extrapolate from this to roles which may relate to protection against neurodegeneration.

Overexpression of the PTPN22 Autoimmune Risk Variant LYP-620W Fails to Restrain Human CD4+ T Cell Activation

A missense mutation (R620W) of protein tyrosine phosphatase nonreceptor type 22 (PTPN22), which encodes lymphoid-tyrosine phosphatase (LYP), confers genetic risk for multiple autoimmune diseases including type 1 diabetes. LYP has been putatively demonstrated to attenuate proximal T and BCR signaling. However, limited data exist regarding PTPN22 expression within primary T cell subsets and the impact of the type 1 diabetes risk variant on human T cell activity. In this study, we demonstrate endogenous PTPN22 is differentially expressed and dynamically controlled following activation. From control subjects homozygous for the nonrisk allele, we observed 2.1- (p < 0.05) and 3.6-fold (p < 0.001) more PTPN22 transcripts in resting CD4⁺ memory and regulatory T cells (Tregs), respectively, over naive CD4⁺ T cells, with expression peaking 24 h postactivation. When LYP was overexpressed in conventional CD4⁺ T cells, TCR signaling and activation were blunted by LYP-620R (p < 0.001) but only modestly affected by the LYP-620W risk variant versus mock-transfected control, with similar results observed in Tregs. LYP overexpression only impacted proliferation following activation by APCs but not anti-CD3- and anti-CD28-coated microbeads, suggesting LYP modulation of pathways other than TCR. Notably, proliferation was significantly lower with LYP-620R than with LYP-620W overexpression in conventional CD4⁺ T cells but was similar in Treg. These data indicate that the LYP-620W variant is hypomorphic in the context of human CD4⁺ T cell activation and may have important implications for therapies seeking to restore immunological tolerance in autoimmune disorders.

A graph centrality-based approach for candidate gene prediction for type 1 diabetes

Type 1 diabetes mellitus (T1DM) or insulin-dependent diabetes is an autoimmune disease that may pose life-threatening situations to individuals. In most cases, cytotoxic T lymphocytes (CTLs) promotes killing of islets of Langerhans in the pancreas, which harbour insulin-producing beta cells. The trigger for autoimmune attack is still unclear; therefore, identifying and targeting candidate genes are imperative to hinder its deleterious effects. In the present study, we focused on identification of new candidate genes for T1DM. For our study, we exclusively selected immune-related genes as they play a crucial role in T1DM. We constructed and analysed a human immunome signalling network (directed network) to identify the new candidate genes through various graph centrality measures combining with Gene Ontology (GO). As a result, we identified 4 new candidate genes which may act as potential drug targets for T1DM. We further validated for their disease relevance through literature survey and pathway analysis and found that 3 out of 4 predicted genes mirrored their well-established roles as potential targets for T1DM.

The long non-coding RNA βFaar regulates islet β-cell function and survival during obesity in mice

Despite obesity being a predisposing factor for pancreatic β-cell dysfunction and loss, the mechanisms underlying its negative effect on insulin-secreting cells remain poorly understood. In this study, we identify an islet-enriched long non-coding RNA (lncRNA), which we name β-cell function and apoptosis regulator (βFaar). βFaar is dramatically downregulated in the islets of the obese mice, and a low level of βFaar is necessary for the development of obesity-associated β-cell dysfunction and apoptosis. Mechanistically, βFaar promote the synthesis and secretion of insulin by upregulating islet-specific genes Ins2, NeuroD1, and Creb1 through sponging miR-138-5p. In addition, using quantitative mass spectrometry, we identify TRAF3IP2 and SMURF1 as interacting proteins that are specifically associated with βFaar. We demonstrate that SMURF1 ubiquitin ligase activity is essential for TRAF3IP2 ubiquitination and activation of NF-κB-mediate β-cell apoptosis. Our experiments provide direct evidence that dysregulated βFaar contributes to the development of obesity-induced β-cell injury and apoptosis.

Beta-cell function is often impaired in obesity through incompletely understood mechanisms. Here the authors show that the long noncoding RNA βFaar is reduced by diet-induced obesity in mice, which leads to impaired beta-cell function via miR-138-5p and survival via TRAF3 Interacting Protein 2.

Parallel Multi-Omics in High-Risk Subjects for the Identification of Integrated Biomarker Signatures of Type 1 Diabetes

BACKGROUND

Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics.

METHODS

Blood from human subjects at high risk for T1D (and healthy controls; n = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to controls.

RESULTS

The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples without exception. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. IPA-predicted candidate biomarkers were used to construct a putative integrated signature containing several miRNAs and metabolite/lipid features in the at-risk subjects.

CONCLUSIONS

Preliminary parallel quadra-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and highlighted the potential for identifying associated integrated biomarker signatures. With further development and validation in larger cohorts, parallel multi-omics could ultimately facilitate the classification of T1D progressors from non-progressors.

Modeling different types of diabetes using human pluripotent stem cells

Diabetes mellitus (DM) is a metabolic disease characterized by chronic hyperglycemia as a result of progressive loss of pancreatic β cells, which could lead to several debilitating complications. Different paths, triggered by several genetic and environmental factors, lead to the loss of pancreatic β cells and/or function. Understanding these many paths to β cell damage or dysfunction could help in identifying therapeutic approaches specific for each path. Most of our knowledge about diabetes pathophysiology has been obtained from studies on animal models, which do not fully recapitulate human diabetes phenotypes. Currently, human pluripotent stem cell (hPSC) technology is a powerful tool for generating in vitro human models, which could provide key information about the disease pathogenesis and provide cells for personalized therapies. The recent progress in generating functional hPSC-derived β cells in combination with the rapid development in genomic and genome-editing technologies offer multiple options to understand the cellular and molecular mechanisms underlying the development of different types of diabetes. Recently, several in vitro hPSC-based strategies have been used for studying monogenic and polygenic forms of diabetes. This review summarizes the current knowledge about different hPSC-based diabetes models and how these models improved our current understanding of the pathophysiology of distinct forms of diabetes. Also, it highlights the progress in generating functional β cells in vitro, and discusses the current challenges and future perspectives related to the use of the in vitro hPSC-based strategies.

Identifying the 'Achilles heel' of type 1 diabetes

When Thetis dipped her son Achilles into the River Styx to make him immortal, she held him by the heel, which was not submerged, and thus created a weak spot that proved deadly for Achilles. Millennia later, Achilles heel is part of today's lexicon meaning an area of weakness or a vulnerable spot that causes failure. Also implied is that an Achilles heel is often missed, forgotten or under-appreciated until it is under attack, and then failure is fatal. Paris killed Achilles with an arrow 'guided by the Gods'. Understanding the pathogenesis of type 1 diabetes (T1D) in order to direct therapy for prevention and treatment is a major goal of research into T1D. At the International Congress of the Immunology of Diabetes Society, 2018, five leading experts were asked to present the case for a particular cell/element that could represent 'the Achilles heel of T1D'. These included neutrophils, B cells, CD8⁺ T cells, regulatory CD4⁺ T cells, and enteroviruses, all of which have been proposed to play an important role in the pathogenesis of type 1 diabetes. Did a single entity emerge as 'the' Achilles heel of T1D? The arguments are summarized here, to make this case.

The β-Cell Genomic Landscape in T1D: Implications for Disease Pathogenesis

PURPOSE OF REVIEW

Type 1 diabetes (T1D) develops as a consequence of a combination of genetic predisposition and environmental factors. Combined, these events trigger an autoimmune disease that results in progressive loss of pancreatic β cells, leading to insulin deficiency. This article reviews the current knowledge on the genetics of T1D with a specific focus on genetic variation in pancreatic islet regulatory networks and its implication to T1D risk and disease development.

RECENT FINDINGS

Accumulating evidence suggest an active role of β cells in T1D pathogenesis. Based on such observation several studies aimed in mapping T1D risk variants acting at the β cell level. Such studies unravel T1D risk loci shared with type 2 diabetes (T2D) and T1D risk variants potentially interfering with β-cell responses to external stimuli. The characterization of regulatory genomics maps of disease-relevant states and cell types can be used to elucidate the mechanistic role of β cells in the pathogenesis of T1D.

The Rac2 GTPase contributes to cathepsin H-mediated protection against cytokine-induced apoptosis in insulin-secreting cells

The type 1 diabetes (T1D) risk locus on chromosome 15q25.1 harbors the candidate gene CTSH (cathepsin H). We previously demonstrated that CTSH regulates β-cell function in vitro and in vivo. CTSH overexpression protected insulin-secreting INS-1 cells against cytokine-induced apoptosis. The purpose of the present study was to identify the genes through which CTSH mediates its protective effects. Microarray analysis identified 63 annotated genes differentially expressed between CTSH-overexpressing INS-1 cells and control cells treated with interleukin-1β and interferon-γ for up to 16h. Permutation test identified 10 significant genes across all time-points: Elmod1, Fam49a, Gas7, Gna15, Msrb3, Nox1, Ptgs1, Rac2, Scn7a and Ttn. Pathway analysis identified the "Inflammation mediated by chemokine and cytokine signaling pathway" with Gna15, Ptgs1 and Rac2 as significant. Knockdown of Rac2 abolished the protective effect of CTSH overexpression on cytokine-induced apoptosis, suggesting that the small GTPase and T1D candidate gene Rac2 contributes to the anti-apoptotic effect of CTSH.

Molecular and Functional Diversity of Distinct Subpopulations of the Stressed Insulin-Secreting Cell's Vesiculome

Beta cell failure and apoptosis following islet inflammation have been associated with autoimmune type 1 diabetes pathogenesis. As conveyors of biological active material, extracellular vesicles (EV) act as mediators in communication with immune effectors fostering the idea that EV from inflamed beta cells may contribute to autoimmunity. Evidence accumulates that beta exosomes promote diabetogenic responses, but relative contributions of larger vesicles as well as variations in the composition of the beta cell's vesiculome due to environmental changes have not been explored yet. Here, we made side-by-side comparisons of the phenotype and function of apoptotic bodies (AB), microvesicles (MV) and small EV (sEV) isolated from an equal amount of MIN6 beta cells exposed to inflammatory, hypoxic or genotoxic stressors. Under normal conditions, large vesicles represent 93% of the volume, but only 2% of the number of the vesicles. Our data reveal a consistently higher release of AB and sEV and to a lesser extent of MV, exclusively under inflammatory conditions commensurate with a 4-fold increase in the total volume of the vesiculome and enhanced export of immune-stimulatory material including the autoantigen insulin, microRNA, and cytokines. Whilst inflammation does not change the concentration of insulin inside the EV, specific Toll-like receptor-binding microRNA sequences preferentially partition into sEV. Exposure to inflammatory stress engenders drastic increases in the expression of monocyte chemoattractant protein 1 in all EV and of interleukin-27 solely in AB suggesting selective sorting toward EV subspecies. Functional in vitro assays in mouse dendritic cells and macrophages reveal further differences in the aptitude of EV to modulate expression of cytokines and maturation markers. These findings highlight the different quantitative and qualitative imprints of environmental changes in subpopulations of beta EV that may contribute to the spread of inflammation and sustained immune cell recruitment at the inception of the (auto-) immune response.

Systems-level differential gene expression analysis reveals new genetic variants of oral cancer

Oral cancer (OC) ranked as eleventh malignancy worldwide, with the increasing incidence among young patients. Limited understanding of complications in cancer progression, its development system, and their interactions are major restrictions towards the progress of optimal and effective treatment strategies. The system-level approach has been designed to explore genetic complexity of the disease and to identify novel oral cancer related genes to detect genomic alterations at molecular level, through cDNA differential analysis. We analyzed 21 oral cancer-related cDNA datasets and listed 30 differentially expressed genes (DEGs). Among 30, we found 6 significant DEGs including CYP1A1, CYP1B1, ADCY2, C7, SERPINB5, and ANAPC13 and studied their functional role in OC. Our genomic and interactive analysis showed significant enrichment of xenobiotics metabolism, p53 signaling pathway and microRNA pathways, towards OC progression and development. We used human proteomic data for post-translational modifications to interpret disease mutations and inter-individual genetic variations. The mutational analysis revealed the sequence predicted disordered region of 14%, 12.5%, 10.5% for ADCY2, CYP1B1, and C7 respectively. The MiRNA target prediction showed functional molecular annotation including specific miRNA-targets hsa-miR-4282, hsa-miR-2052, hsa-miR-216a-3p, for CYP1B1, C7, and ADCY2 respectively associated with oral cancer. We constructed the system level network and found important gene signatures. The drug-gene interaction of OC source genes with seven FDA approved OC drugs help to design or identify new drug target or establishing novel biomedical linkages regarding disease pathophysiology. This investigation demonstrates the importance of system genetics for identifying 6 OC genes (CYP1A1, CYP1B1, ADCY2, C7, SERPINB5, and ANAPC13) as potential drugs targets. Our integrative network-based system-level approach would help to find the genetic variants of OC that can accelerate drug discovery outcomes to develop a better understanding regarding treatment strategies for many cancer types.

In silico analysis reveals interrelation of enriched pathways and genes in type 1 diabetes

Type 1 diabetes (T1D) is a multifactorial, polygenic complex autoimmune disease damaging pancreatic islet β cells. Numerous genes linked to T1D have been discovered through genetical studies, GWAS and polymorphisms. Most genetical studies focused on independent genes while others overemphasized on SNPs. Here, a collective analysis of documented T1D-associated genes was performed using bioinformatics tools. Enriched biological pathways, functions, enrichment clustering, networks and interactomes were analysed. Besides, meta-analyses of T1D-associated genes and T1D-related genes from SNPs were investigated to find common genes, pathways, enrichment and interrelationships. Notable enriched pathways comprised of cytokine-mediated signalling, cytokine production, interferon gamma production, myeloid leukocyte activation, activation of immune response, lymphocyte activation, adaptive immune response, Th17 cell differentiation etc. Enrichment analysis of T1D-associated genes emphasized the role of immune-linked machineries in metabolism, disease progression and aetiology of type 1 diabetes. Interactome analysis revealed overrepresentation of T1D-associated genes compared with T1D-related genes from SNPs. MCODE components highlighted the significance of pathways linked to vitamin D metabolism, signalling by interleukins, toll-like receptors, chemokines, PD-1, NOTCH, antigen processes etc. About 153 genes from MCODE complexes representing enriched pathways of T1D-associated genes and T1D-related genes from SNPs play a crucial role and may be important for further investigations. The information may be valuable for designing precision medicine-based therapeutics.

Identification of potential markers for type 2 diabetes mellitus via bioinformatics analysis

Type 2 diabetes mellitus (T2DM) is a multifactorial and multigenetic disease, and its pathogenesis is complex and largely unknown. In the present study, microarray data (GSE201966) of β-cell enriched tissue obtained by laser capture microdissection were downloaded, including 10 control and 10 type 2 diabetic subjects. A comprehensive bioinformatics analysis of microarray data in the context of protein-protein interaction (PPI) networks was employed, combined with subcellular location information to mine the potential candidate genes for T2DM and provide further insight on the possible mechanisms involved. First, differential analysis screened 108 differentially expressed genes. Then, 83 candidate genes were identified in the layered network in the context of PPI via network analysis, which were either directly or indirectly linked to T2DM. Of those genes obtained through literature retrieval analysis, 27 of 83 were involved with the development of T2DM; however, the rest of the 56 genes need to be verified by experiments. The functional analysis of candidate genes involved in a number of biological activities, demonstrated that 46 upregulated candidate genes were involved in ‘inflammatory response’ and ‘lipid metabolic process’, and 37 downregulated candidate genes were involved in ‘positive regulation of cell death’ and ‘positive regulation of cell proliferation’. These candidate genes were also involved in different signaling pathways associated with ‘PI3K/Akt signaling pathway’, ‘Rap1 signaling pathway’, ‘Ras signaling pathway’ and ‘MAPK signaling pathway’, which are highly associated with the development of T2DM. Furthermore, a microRNA (miR)-target gene regulatory network and a transcription factor-target gene regulatory network were constructed based on miRNet and NetworkAnalyst databases, respectively. Notably, hsa-miR-192-5p, hsa-miR-124-5p and hsa-miR-335-5p appeared to be involved in T2DM by potentially regulating the expression of various candidate genes, including procollagen C-endopeptidase enhancer 2, connective tissue growth factor and family with sequence similarity 105, member A, protein phosphatase 1 regulatory inhibitor subunit 1 A and C-C motif chemokine receptor 4. Smad5 and Bcl6, as transcription factors, are regulated by ankyrin repeat domain 23 and transmembrane protein 37, respectively, which might also be used in the molecular diagnosis and targeted therapy of T2DM. Taken together, the results of the present study may offer insight for future genomic-based individualized treatment of T2DM and help determine the underlying molecular mechanisms that lead to T2DM.

Precision medicine - networks to the rescue

Genetic variants are often not predictive of the phenotypic outcome. Individuals carrying the same pathogenic variant, associated with Mendelian or complex disease, can manifest to different extents, from severe-to-mild to no disease. Improving the accuracy of predicted clinical manifestations of genetic variants has emerged as one of the biggest challenges in precision medicine, which can only be addressed by understanding the mechanisms underlying genotype-phenotype relationships. Efforts to understand the molecular basis of these relationships have identified complex systems of interacting biomolecules that underlie cellular function. Here, we review recent advances in how modeling cellular systems as networks of interacting proteins has fueled identification of disease-associated processes, delineation of underlying molecular mechanisms, and prediction of the pathogenicity of variants. This review is intended to be inspiring for clinicians, geneticists, and network biologists alike who aim to jointly advance our understanding of human disease and accelerate progress toward precision medicine.

Advances in Knowledge of Candidate Genes Acting at the Beta-Cell Level in the Pathogenesis of T1DM

T1DM (type 1 diabetes mellitus), which results from the irreversible elimination of beta-cells mediated by autoreactive T cells, is defined as an autoimmune disease. It is widely accepted that T1DM is caused by a combination of genetic and environmental factors, but the precise underlying molecular mechanisms are still unknown. To date, more than 50 genetic risk regions contributing to the pathogenesis of T1DM have been identified by GWAS (genome-wide association studies). Notably, more than 60% of the identified candidate genes are expressed in islets and beta-cells, which makes it plausible that these genes act at the beta-cell level and play a key role in the pathogenesis of T1DM. In this review, we focus on the current status of candidate genes that act at the beta-cell level by regulating the innate immune response and antiviral activity, affecting susceptibility to proapoptotic stimuli and influencing the pancreatic beta-cell phenotype.

Interleukin-27 Is Essential for Type 1 Diabetes Development and Sjögren Syndrome-like Inflammation

Human genetic studies implicate interleukin-27 (IL-27) in the pathogenesis of type 1 diabetes (T1D), but the underlying mechanisms remain largely unexplored. To further define the role of IL-27 in T1D, we generated non-obese diabetic (NOD) mice deficient in IL-27 or IL-27Rα. In contrast to wild-type NOD mice, both NOD.Il27-/- and NOD.Il27ra-/- strains are completely resistant to T1D. IL-27 from myeloid cells and IL-27 signaling in T cells are critical for T1D development. IL-27 directly alters the balance of regulatory T cells (Tregs) and T helper 1 (Th1) cells in pancreatic islets, which in turn modulates the diabetogenic activity of CD8 T cells. IL-27 also directly enhances the effector function of CD8 T cells within pancreatic islets. In addition to T1D, IL-27 signaling in T cells is also required for lacrimal and salivary gland inflammation in NOD mice. Our study reveals that IL-27 contributes to autoimmunity in NOD mice through multiple mechanisms and provides substantial evidence to support its pathogenic role in human T1D.

Graph cluster approach in identifying novel proteins and significant pathways involved in polycystic ovary syndrome

RESEARCH QUESTION

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with diverse clinical implications, such as infertility, metabolic disorders, cardiovascular diseases and psychological problems among others. The heterogeneity of conditions found in PCOS contribute to its various phenotypes, leading to difficulties in identifying proteins involved in this abnormality. Several studies, however, have shown the feasibility in identifying molecular evidence underlying other diseases using graph cluster analysis. Therefore, is it possible to identify proteins and pathways related to PCOS using the same approach?

METHODS

Known PCOS-related proteins (PCOSrp) from PCOSBase and DisGeNET were integrated with protein-protein interactions (PPI) information from Human Integrated Protein-Protein Interaction reference to construct a PCOS PPI network. The network was clustered with DPClusO algorithm to generate clusters, which were evaluated using Fisher's exact test. Pathway enrichment analysis using gProfileR was conducted to identify significant pathways.

RESULTS

The statistical significance of the identified clusters has successfully predicted 138 novel PCOSrp with 61.5% reliability and, based on Cronbach's alpha, this prediction is acceptable. Androgen signalling pathway and leptin signalling pathway were among the significant PCOS-related pathways corroborating the information obtained from the clinical observation, where androgen signalling pathway is responsible in producing male hormones in women with PCOS, whereas leptin signalling pathway is involved in insulin sensitivity.

CONCLUSIONS

These results show that graph cluster analysis can provide additional insight into the pathobiology of PCOS, as the pathways identified as statistically significant correspond to earlier biological studies. Therefore, integrative analysis can reveal unknown mechanisms, which may enable the development of accurate diagnosis and effective treatment in PCOS.

Human Leukocyte Antigen (HLA) and Islet Autoantibodies Are Tools to Characterize Type 1 Diabetes in Arab Countries: Emphasis on Kuwait

The incidence rate of type 1 diabetes in Kuwait had been increasing exponentially and has doubled in children ≤ 14 years old within almost two decades. Therefore, there is a dire need for a careful systematic familial cohort study. Several immunogenetic factors affect the pathogenesis of the disease. The human leukocyte antigen (HLA) accounts for the major genetic susceptibility to the disease. The triggering agents initiate disease onset by type 1 destruction of pancreatic β-cells. Both HLA and anti-islet antibodies can be used to characterize, predict susceptibility to the disease, innovate, or delay the β-cell destruction. Evidence from prospective longitudinal studies suggested that the underlying disease process represents a continuum that begins before the symptoms are clinically evident. Autoimmunity of the functional pancreatic β-cells results in symptomatic type 1 diabetes and lifelong insulin dependence. The autoantibodies against glutamic acid decarboxylase (GADA), insulinoma antigen-2 (IA-2A), insulin (IAA), and zinc transporter-8 (ZnT-8A) comprise the most reliable biomarkers for type 1 diabetes in both children and adults. Although Kuwait is the second among the top 10 countries with a high incidence rate of type 1 diabetes, there have been no proper diagnostic and prediction tools as per the World Health Organization. The Kuwaiti Type 1 Diabetes Study (KADS) was initiated to understand the disease pathogenesis as well as the HLA and anti-islet autoantibody profile of type 1 diabetes in Kuwait. Understanding the disease sequela in a homogenous gene pool and highly consanguineous population of Kuwaitis could help solve the challenges and pathogenesis, as well as hasten the prevention, of type 1 diabetes.

Loss of MafA and MafB expression promotes islet inflammation

Maf transcription factors are critical regulators of beta-cell function. We have previously shown that reduced MafA expression in human and mouse islets is associated with a pro-inflammatory gene signature. Here, we investigate if the loss of Maf transcription factors induced autoimmune processes in the pancreas. Transcriptomics analysis showed expression of pro-inflammatory as well as immune cell marker genes. However, clusters of CD4+ T and B220+ B cells were associated primarily with adult MafA^−/−MafB^+/−, but not MafA^−/− islets. MafA expression was detected in the thymus, lymph nodes and bone marrow suggesting a novel role of MafA in regulating immune-cell function. Analysis of pancreatic lymph node cells showed activation of CD4+ T cells, but lack of CD8+ T cell activation which also coincided with an enrichment of naïve CD8+ T cells. Further analysis of T cell marker genes revealed a reduction of T cell receptor signaling gene expression in CD8, but not in CD4+ T cells, which was accompanied with a defect in early T cell receptor signaling in mutant CD8+ T cells. These results suggest that loss of MafA impairs both beta- and T cell function affecting the balance of peripheral immune responses against islet autoantigens, resulting in local inflammation in pancreatic islets.

Statistical Association Mapping of Population-Structured Genetic Data

Association mapping of genetic diseases has attracted extensive research interest during the recent years. However, most of the methodologies introduced so far suffer from spurious inference of the associated sites due to population inhomogeneities. In this paper, we introduce a statistical framework to compensate for this shortcoming by equipping the current methodologies with a state-of-the-art clustering algorithm being widely used in population genetics applications. The proposed framework jointly infers the disease-associated factors and the hidden population structures. In this regard, a Markov Chain-Monte Carlo (MCMC) procedure has been employed to assess the posterior probability distribution of the model parameters. We have implemented our proposed framework on a software package whose performance is extensively evaluated on a number of synthetic datasets, and compared to some of the well-known existing methods such as STRUCTURE. It has been shown that in extreme scenarios, up to $10-15$10-15 percent of improvement in the inference accuracy is achieved with a moderate increase in computational complexity.

The genetic architecture of type 1 diabetes mellitus

Type 1 diabetes mellitus (T1D) is a complex autoimmune disorder characterised by loss of the insulin-producing pancreatic beta cells in genetically predisposed individuals, ultimately resulting in insulin deficiency and hyperglycaemia. T1D is most common among children and young adults, and the incidence is on the rise across the world. The aetiology of T1D is hypothesized to involve genetic and environmental factors that result in the T-cell mediated destruction of pancreatic beta cells. There is a strong genetic risk to T1D; with genome-wide association studies (GWAS) identifying over 60 susceptibility regions within the human genome which are marked by single nucleotide polymorphisms (SNPs). Here, we review what is currently known about the genetics of T1D. We argue that advancing our understanding of the aetiology and pathogenesis of T1D will require the integration of genome biology (omics-data) with GWAS data, thereby making it possible to elucidate the putative gene regulatory networks modulated by disease-associated SNPs. This approach has a potential to revolutionize clinical management of T1D in an era of precision medicine.

Analyzing of Molecular Networks for Human Diseases and Drug Discovery

Molecular networks represent the interactions and relations of genes/proteins, and also encode molecular mechanisms of biological processes, development and diseases. Among the molecular networks, protein-protein Interaction Networks (PINs) have become effective platforms for uncovering the molecular mechanisms of diseases and drug discovery. PINs have been constructed for various organisms and utilized to solve many biological problems. In human, most proteins present their complex functions by interactions with other proteins, and the sum of these interactions represents the human protein interactome. Especially in the research on human disease and drugs, as an emerging tool, the PIN provides a platform to systematically explore the molecular complexities of specific diseases and the references for drug design. In this review, we summarized the commonly used approaches to aid disease research and drug discovery with PINs, including the network topological analysis, identification of novel pathways, drug targets and sub-network biomarkers for diseases. With the development of bioinformatic techniques and biological networks, PINs will play an increasingly important role in human disease research and drug discovery.

TRAF3IP2, a novel therapeutic target in glioblastoma multiforme

Glioblastoma multiforme (glioblastoma) remains one of the deadliest cancers. Pro-inflammatory and pro-tumorigenic mediators present in tumor microenvironment (TME) facilitate communication between tumor cells and adjacent non-malignant cells, resulting in glioblastoma growth. Since a majority of these mediators are products of NF-κB- and/or AP-1-responsive genes, and as TRAF3 Interacting Protein 2 (TRAF3IP2) is an upstream regulator of both transcription factors, we hypothesized that targeting TRAF3IP2 blunts tumor growth by inhibiting NF-κB and pro-inflammatory/pro-tumorigenic mediators. Our in vitro data demonstrate that similar to primary glioblastoma tumor tissues, malignant glioblastoma cell lines (U87 and U118) express high levels of TRAF3IP2. Silencing TRAF3IP2 expression inhibits basal and inducible NF-κB activation, induction of pro-inflammatory mediators, clusters of genes involved in cell cycle progression and angiogenesis, and formation of spheroids. Additionally, silencing TRAF3IP2 significantly increases apoptosis. In vivo studies indicate TRAF3IP2-silenced U87 cells formed smaller tumors. Additionally, treating existing tumors formed by wild type U87 cells with lentiviral TRAF3IP2 shRNA markedly regresses their size. Analysis of residual tumors revealed reduced expression of pro-inflammatory/pro-tumorigenic/pro-angiogenic mediators and kinesins. In contrast, the expression of IL-10, an anti-inflammatory cytokine, was increased. Together, these novel data indicate that TRAF3IP2 is a master regulator of malignant signaling in glioblastoma, and its targeting modulates the TME and inhibits tumor growth by suppressing the expression of mediators involved in inflammation, angiogenesis, growth, and malignant transformation. Our data identify TRAF3IP2 as a potential therapeutic target in glioblastoma growth and dissemination.

Association of protein tyrosine phosphatase non-receptor type 22 gene functional variant C1858T, HLA-DQ/DR genotypes and autoantibodies with susceptibility to type-1 diabetes mellitus in Kuwaiti Arabs

The incidence of type-1 Diabetes Mellitus (T1DM) has increased steadily in Kuwait during recent years and it is now considered amongst the high-incidence countries. An interaction between susceptibility genes, immune system mediators and environmental factors predispose susceptible individuals to T1DM. We have determined the prevalence of protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene functional variant (C1858T; R620W, rs2476601), HLA-DQ and DR alleles and three autoantibodies in Kuwaiti children with T1DM to evaluate their impact on genetic predisposition of the disease. This study included 253 Kuwaiti children with T1DM and 214 ethnically matched controls. The genotypes of PTPN22 gene functional variant C1858T (R620W; rs2476601) were detected by PCR-RFLP method and confirmed by DNA sequencing. HLA-DQ and DR alleles were determined by sequence-specific PCR. Three autoantibodies were detected in the T1DM patients using radio-immunoassays. A significant association was detected between the variant genotype of the PTPN22 gene (C1858T, rs2476601) and T1DM in Kuwaiti Arabs. HLA-DQ2 and DQ8 alleles showed a strong association with T1DM. In T1DM patients which carried the variant TT-genotype of the PTPN22 gene, 93% had at least one DQ2 allele and 60% carried either a DQ2 or a DQ8 allele. Amongst the DR alleles, the DR3-DRB5, DR3-3, DR3-4 and DR4-4 showed a strong association with T1DM. Majority of T1DM patients who carried homozygous variant (TT) genotype of the PTPN22 gene had either DR3-DRB5 or DRB3-DRB4 genotypes. In T1DM patients who co-inherited the high risk HLA DQ, DR alleles with the variant genotype of PTPN22 gene, the majority were positive for three autoantibodies. Our data demonstrate that the variant T-allele of the PTPN22 gene along with HLA-DQ2 and DQ8 alleles constitute significant determinants of genetic predisposition of T1DM in Kuwaiti children.

Type 1 diabetes genome-wide association studies: not to be lost in translation

Genetic studies have identified >60 loci associated with the risk of developing type 1 diabetes (T1D). The vast majority of these are identified by genome-wide association studies (GWAS) using large case-control cohorts of European ancestry. More than 80% of the heritability of T1D can be explained by GWAS data in this population group. However, with few exceptions, their individual contribution to T1D risk is low and understanding their function in disease biology remains a huge challenge. GWAS on its own does not inform us in detail on disease mechanisms, but the combination of GWAS data with other omics-data is beginning to advance our understanding of T1D etiology and pathogenesis. Current knowledge supports the notion that genetic variation in both pancreatic β cells and in immune cells is central in mediating T1D risk. Advances, perspectives and limitations of GWAS are discussed in this review.

The Genetic Architecture of Type 1 Diabetes

Type 1 diabetes (T1D) is classically characterised by the clinical need for insulin, the presence of disease-associated serum autoantibodies, and an onset in childhood. The disease, as with other autoimmune diseases, is due to the interaction of genetic and non-genetic effects, which induce a destructive process damaging insulin-secreting cells. In this review, we focus on the nature of this interaction, and how our understanding of that gene-environment interaction has changed our understanding of the nature of the disease. We discuss the early onset of the disease, the development of distinct immunogenotypes, and the declining heritability with increasing age at diagnosis. Whilst Human Leukocyte Antigens (HLA) have a major role in causing T1D, we note that some of these HLA genes have a protective role, especially in children, whilst other non-HLA genes are also important. In adult-onset T1D, the disease is often not insulin-dependent at diagnosis, and has a dissimilar immunogenotype with reduced genetic predisposition. Finally, we discuss the putative nature of the non-genetic factors and how they might interact with genetic susceptibility, including preliminary studies of the epigenome associated with T1D.

Early prediction of autoimmune (type 1) diabetes

Underlying type 1 diabetes is a genetic aetiology dominated by the influence of specific HLA haplotypes involving primarily the class II DR-DQ region. In genetically predisposed children with the DR4-DQ8 haplotype, exogenous factors, yet to be identified, are thought to trigger an autoimmune reaction against insulin, signalled by insulin autoantibodies as the first autoantibody to appear. In children with the DR3-DQ2 haplotype, the triggering reaction is primarily against GAD signalled by GAD autoantibodies (GADA) as the first-appearing autoantibody. The incidence rate of insulin autoantibodies as the first-appearing autoantibody peaks during the first years of life and declines thereafter. The incidence rate of GADA as the first-appearing autoantibody peaks later but does not decline. The first autoantibody may variably be followed, in an apparently non-HLA-associated pathogenesis, by a second, third or fourth autoantibody. Although not all persons with a single type of autoantibody progress to diabetes, the presence of multiple autoantibodies seems invariably to be followed by loss of functional beta cell mass and eventually by dysglycaemia and symptoms. Infiltration of mononuclear cells in and around the islets appears to be a late phenomenon appearing in the multiple-autoantibody-positive with dysglycaemia. As our understanding of the aetiology and pathogenesis of type 1 diabetes advances, the improved capability for early prediction should guide new strategies for the prevention of type 1 diabetes.

Abnormalities in alternative splicing in diabetes: therapeutic targets

Diabetes mellitus (DM) is a non-communicable, metabolic disorder that affects 416 million individuals worldwide. Type 2 diabetes contributes to a vast 85-90% of the diabetes incidences while 10-15% of patients suffer from type 1 diabetes. These two predominant forms of DM cause a significant loss of functional pancreatic β-cell mass causing different degrees of insulin deficiency, most likely, due to increased β-cell apoptosis. Treatment options involve the use of insulin sensitisers, α-glucosidase inhibitors, and β-cell secretagogues which are often expensive, limited in efficacy and carry detrimental adverse effects. Cost-effective options for treatment exists in the form of herbal drugs, however, scientific validations of these widely used medicinal plants are still underway. Alternative splicing (AS) is a co-ordinated post-transcriptional process in which a single gene generates multiple mRNA transcripts which results in increased amounts of functionally different protein isoforms and in some cases aberrant splicing leads to metabolic disease. In this review, we explore the association of AS with metabolic alterations in DM and the biological significance of the abnormal splicing of some pathogenic diabetes-related genes. An understanding of the molecular mechanism behind abnormally spliced transcripts will aid in the development of new diagnostic, prognostic and therapeutic tools.

Identification of new key genes for type 1 diabetes through construction and analysis of protein-protein interaction networks based on blood and pancreatic islet transcriptomes

BACKGROUND

Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic β-cells are destroyed by infiltrating immune cells. Bilateral cooperation of pancreatic β-cells and immune cells has been proposed in the progression of T1D, but as yet no systems study has investigated this possibility. The aims of the study were to elucidate the underlying molecular mechanisms and identify key genes associated with T1D risk using a network biology approach.

METHODS

Interactome (protein-protein interaction [PPI]) and transcriptome data were integrated to construct networks of differentially expressed genes in peripheral blood mononuclear cells (PBMCs) and pancreatic β-cells. Centrality, modularity, and clique analyses of networks were used to get more meaningful biological information.

RESULTS

Analysis of genes expression profiles revealed several cytokines and chemokines in β-cells and their receptors in PBMCs, which is supports the dialogue between these two tissues in terms of PPIs. Functional modules and complexes analysis unraveled most significant biological pathways such as immune response, apoptosis, spliceosome, proteasome, and pathways of protein synthesis in the tissues. Finally, Y-box binding protein 1 (YBX1), SRSF protein kinase 1 (SRPK1), proteasome subunit alpha1/ 3, (PSMA1/3), X-ray repair cross complementing 6 (XRCC6), Cbl proto-oncogene (CBL), SRC proto-oncogene, non-receptor tyrosine kinase (SRC), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), phospholipase C gamma 1 (PLCG1), SHC adaptor protein1 (SHC1) and ubiquitin conjugating enzyme E2 N (UBE2N) were identified as key markers that were hub-bottleneck genes involved in functional modules and complexes.

CONCLUSIONS

This study provide new insights into network biomarkers that may be considered potential therapeutic targets.

Pannexin-2-deficiency sensitizes pancreatic β-cells to cytokine-induced apoptosis in vitro and impairs glucose tolerance in vivo

Pannexins (Panx's) are membrane proteins involved in a variety of biological processes, including cell death signaling and immune functions. The role and functions of Panx's in pancreatic β-cells remain to be clarified. Here, we show Panx1 and Panx2 expression in isolated islets, primary β-cells, and β-cell lines. The expression of Panx2, but not Panx1, was downregulated by interleukin-1β (IL-1β) plus interferon-γ (IFNγ), two pro-inflammatory cytokines suggested to contribute to β-cell demise in type 1 diabetes (T1D). siRNA-mediated knockdown (KD) of Panx2 aggravated cytokine-induced apoptosis in rat INS-1E cells and primary rat β-cells, suggesting anti-apoptotic properties of Panx2. An anti-apoptotic function of Panx2 was confirmed in isolated islets from Panx2^-/- mice and in human EndoC-βH1 cells. Panx2 KD was associated with increased cytokine-induced activation of STAT3 and higher expression of inducible nitric oxide synthase (iNOS). Glucose-stimulated insulin release was impaired in Panx2^-/- islets, and Panx2^-/- mice subjected to multiple low-dose Streptozotocin (MLDS) treatment, a model of T1D, developed more severe diabetes compared to wild type mice. These data suggest that Panx2 is an important regulator of the insulin secretory capacity and apoptosis in pancreatic β-cells.

Patient complexity and genotype-phenotype correlations in biliary atresia: a cross-sectional analysis

Background

Biliary Atresia (BA) is rare and genetically complex, and the pathogenesis is elusive. The disease course is variable and can represent heterogeneity, which hinders effective disease management. Deciphering the BA phenotypic variance is a priority in clinics and can be achieved by the integrative analysis of genotype and phenotype. We aim to explore the BA phenotypic features and to delineate the source of its variance.

Methods

The study is a cross-sectional observational study collating with case/control association analysis. One-hundred-and-eighty-one type III non-syndromic BA patients and 431 controls were included for case–control association tests, including 89 patients (47.19% males, born June 15th, 1981 to September 17th, 2007) have detailed clinical records with follow-up of the disease course (median ~17.2 years). BA-association genes from the genome-wide gene-based association test on common genetic variants (CV) and rare copy-number-variants (CNVs) from the genome-wide survey, the later comprise only CNVs > 100 kb and found in the BA patients but not in the local population (N = 1,381) or the database (N = 11,943). Hereby comorbidity is defined as a chronic disease that affects the BA patients but has no known relationship with BA or with the BA treatment. We examined genotype-phenotype correlations of CNVs, connectivity of these novel variants with BA-associated CVs, and their role in the BA candidate gene network.

Results

Of the 89 patients, 41.57% have comorbidities, including autoimmune-allergic disorders (22.47%). They carried 29 BA-private CNVs, including 3 CNVs underpinning the carriers’ immunity comorbidity and one JAG1 micro-deletion. The BA-CNV-intersected genes (N = 102) and the CV-tagged genes (N = 103) were both enriched with immune-inflammatory pathway genes (FDR q < 0.20), and the two gene sets were interconnected (permutation p = 0.039). The molecular network representing CVs and rare-CNV association genes fit into a core/periphery structure, the immune genes and their related modules are found at the coherence core of all connections, suggesting its dominant role in the BA pathogenesis pathway.

Conclusions

The study highlights a patient-complexity phenomenon as a novel BA phenotypic feature, which is underpinned by rare-CNVs that biologically converge with CVs into the immune-inflammatory pathway and drives the BA occurrence and the likely BA association with immune diseases in clinics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-017-0259-0) contains supplementary material, which is available to authorized users.

Dual Role of Act1 in Keratinocyte Differentiation and Host Defense: TRAF3IP2 Silencing Alters Keratinocyte Differentiation and Inhibits IL-17 Responses

TRAF3IP2 is a candidate psoriasis susceptibility gene encoding Act1, an adaptor protein with ubiquitin ligase activity that couples the IL-17 receptor to downstream signaling pathways. We investigated the role of Act1 in keratinocyte responses to IL-17 using a tetracycline inducible short hairpin RNA targeting TRAF3IP2. Tetracycline exposure for 7 days effectively silenced TRAF3IP2 mRNA and Act1 protein, resulting in 761 genes with significant changes in expression (495 down, 266 up; >1.5-fold, P < 0.05). Gene ontology analysis showed that genes affected by TRAF3IP2 silencing are involved in epidermal differentiation, with early differentiation genes (KRT1, KRT10, DSC1, DSG1) being down-regulated and late differentiation genes (SPRR2, SPRR3, LCE3) being up-regulated. AP1 binding sites were enriched upstream of genes up-regulated by TRAF3IP2 silencing. Correspondingly, nuclear expression of FosB and Fra1 was increased in TRAF3IP2-silenced cells. Many genes involved in host defense were induced by IL-17 in a TRAF3IP2-dependent fashion. Inflammatory differentiation conditions (serum addition for 4 days postconfluence) markedly amplified these IL-17 responses and increased basal levels and TRAF3IP2 silencing-dependent up-regulation of multiple late differentiation genes. These findings suggest that TRAF3IP2 may alter both epidermal homeostasis and keratinocyte defense responses to influence psoriasis risk.

Type 1 Diabetes Candidate Genes Linked to Pancreatic Islet Cell Inflammation and Beta-Cell Apoptosis

Type 1 diabetes (T1D) is a chronic immune-mediated disease resulting from the selective destruction of the insulin-producing pancreatic islet β-cells. Susceptibility to the disease is the result of complex interactions between environmental and genetic risk factors. Genome-wide association studies (GWAS) have identified more than 50 genetic regions that affect the risk of developing T1D. Most of these susceptibility loci, however, harbor several genes, and the causal variant(s) and gene(s) for most of the loci remain to be established. A significant part of the genes located in the T1D susceptibility loci are expressed in human islets and β cells and mounting evidence suggests that some of these genes modulate the β-cell response to the immune system and viral infection and regulate apoptotic β-cell death. Here, we discuss the current status of T1D susceptibility loci and candidate genes with focus on pancreatic islet cell inflammation and β-cell apoptosis.

Cellular Signaling Pathways in Insulin Resistance-Systems Biology Analyses of Microarray Dataset Reveals New Drug Target Gene Signatures of Type 2 Diabetes Mellitus

Purpose: Type 2 diabetes mellitus (T2DM) is a chronic and metabolic disorder affecting large set of population of the world. To widen the scope of understanding of genetic causes of this disease, we performed interactive and toxicogenomic based systems biology study to find potential T2DM related genes after cDNA differential analysis.

Methods: From the list of 50-differential expressed genes (p < 0.05), we found 9-T2DM related genes using extensive data mapping. In our constructed gene-network, T2DM-related differentially expressed seeder genes (9-genes) are found to interact with functionally related gene signatures (31-genes). The genetic interaction network of both T2DM-associated seeder as well as signature genes generally relates well with the disease condition based on toxicogenomic and data curation.

Results: These networks showed significant enrichment of insulin signaling, insulin secretion and other T2DM-related pathways including JAK-STAT, MAPK, TGF, Toll-like receptor, p53 and mTOR, adipocytokine, FOXO, PPAR, P13-AKT, and triglyceride metabolic pathways. We found some enriched pathways that are common in different conditions. We recognized 11-signaling pathways as a connecting link between gene signatures in insulin resistance and T2DM. Notably, in the drug-gene network, the interacting genes showed significant overlap with 13-FDA approved and few non-approved drugs. This study demonstrates the value of systems genetics for identifying 18 potential genes associated with T2DM that are probable drug targets.

Conclusions: This integrative and network based approaches for finding variants in genomic data expect to accelerate identification of new drug target molecules for different diseases and can speed up drug discovery outcomes.

Where genes meet environment-integrating the role of gut luminal contents, immunity and pancreas in type 1 diabetes

The rise in new cases of type 1 diabetes (T1D) in genetically susceptible individuals over the past half century has been attributed to numerous environmental "triggers" or promoters such as enteroviruses, diet, and most recently, gut bacteria. No single cause has been identified in humans, likely because there are several pathways by which one can develop T1D. There is renewed attention to the role of the gut and its immune system in T1D pathogenesis based largely on recent animal studies demonstrating that altering the gut microbiota affects diabetes incidence. Although T1D patients display dysbiosis in the gut microbiome, it is unclear whether this is cause or effect. The heart of this question involves several moving parts including numerous risk genes, diet, viruses, gut microbiota, timing, and loss of immune tolerance to β-cells. Most clinical trials have addressed only one aspect of this puzzle using some form of immune suppression, without much success. The key location where our genes meet and deal with the environment is the gastrointestinal tract. The influence of all of its major contents, including microbes, diet, and immune system, must be understood as part of the integrative biology of T1D before we can develop durable means of preventing, treating, or curing this disease. In the present review, we expand our previous gut-centric model based on recent developments in the field.

Incorporation of protein binding effects into likelihood ratio test for exome sequencing data

Statistical association studies are an important tool in detecting novel disease genes. However, for sequencing data, association studies confront the challenge of low power because of relatively small data sample size and rare variants. Incorporating biological information that reflects disease mechanism is likely to strengthen the association evidence of disease genes, and thus increase the power of association studies. In this paper, we annotate non-synonymous single-nucleotide variants according to protein binding sites (BSs) by using a more accurate BS prediction method. We then incorporate this information into association study through a statistical framework of likelihood ratio test (LRT) based on weighted burden score of single-nucleotide variants (SNVs). The strategy is applied to Genetic Analysis Workshop 19 exome-sequencing data for detecting novel genes associated to hypotension. The SNV-weighting LRT idea is empirically verified by the simulated phenotypes (336 cases and 1607 controls), and the weights based on BS annotation are applied to the real phenotypes (394 cases and 1457 controls). Such strategy of weighting the prior information on protein functional sites is shown to be superior to the unweighted LRT and serves as a good complement to the existing association tests. Several putative genes are reported; some of them are functionally related to hypertension according to the previous evidence in the literature.

Of the multiple mechanisms leading to type 1 diabetes, T cell receptor revision may play a prominent role (is type 1 diabetes more than a single disease?)

A single determinant factor for autoimmunity does not exist; disease development probably involves contributions from genetics, the environment and immune dysfunction. Type 1 diabetes is no exception. Genomewide-associated studies (GWAS) analysis in T1D has proved disappointing in revealing contributors to disease prediction; the only reliable marker has been human leucocyte antigen (HLA). Specific HLAs include DR3/DR4/DQ2/DQ8, for example. Because HLA molecules present antigen to T cells, it is reasonable that certain HLA molecules have a higher affinity to present self-antigen. Recent studies have shown that additional polymorphisms in HLA that are restricted to autoimmune conditions are further contributory. A caveat is that not all individuals with the appropriate 'pro-autoimmune' HLA develop an autoimmune disease. Another crucial component is autoaggressive T cells. Finding a biomarker to discriminate autoaggressive T cells has been elusive. However, a subset of CD4 helper cells that express the CD40 receptor have been described as becoming pathogenic. An interesting function of CD40 on T cells is to induce the recombination-activating gene (RAG)1/RAG2 T cell receptor recombination machinery. This observation is contrary to immunology paradigms that changes in TCR molecules cannot take place outside the thymic microenvironment. Alteration in TCR, called TCR revision, not only occurs, but may help to account for the development of autoaggressive T cells. Another interesting facet is that type 1 diabetes (T1D) may be more than a single disease; that is, multiple cellular components contribute uniquely, but result ultimately in the same clinical outcome, T1D. This review considers the process of T cell maturation and how that could favor auto-aggressive T cell development in T1D. The potential contribution of TCR revision to autoimmunity is also considered.

Effects of the genome on immune regulation in type 1 diabetes

Type 1 diabetes (T1DM) is a complex disease, arising through the interaction of an incompletely defined combination of genetic susceptibility and environmental factors. It is well accepted that T1DM results from selective immune-mediated destruction of the insulin-producing β cells in the islets of langerhans. Genetic studies of T1DM have identified several regions of susceptibility and identified major networks and pathways contributing to risk. In this study, we have taken advantages of the Immunochip fine-mapping genotyping data to address different aspects of immune regulation in relation to T1DM. First, we confirm that dense single nucleotide polymorphism (SNP) genotyping of the major histocompatibility complex/human leukocyte antigen (MHC/HLA) region capture the complex genetic contribution of this region to disease risk. Furthermore, it is shown that Immunochip genotyping can translate into a limited number of DRB1 and DQB1 amino acid residues that account for most of the HLA-risk. Second, we use the Immunochip data to look for functional significance by correlation to circulating levels of chemokines and demonstrate that genetic variation at chromosome 2, 3, and 6 correlates with circulating CCL2 and CCL4 in recent onset T1DM patients. Finally, we report that genetic variants predict autoantibody positivity in T1DM cases.