Effect of the PTPN22 and INS risk genotypes on the progression to clinical type 1 diabetes after the initiation of β-cell autoimmunity

Does type 1 diabetes serve as a protective factor against inflammatory bowel disease: A Mendelian randomization study

BACKGROUND

The impact of type 1 diabetes (T1D) on inflammatory bowel disease (IBD) remains unclear.

AIM

To analyze the causal relationship between T1D and IBD using Mendelian ran-domization (MR).

METHODS

Single nucleotide polymorphisms were sourced from FinnGen for T1D, IBD, ulcerative colitis (UC) and Crohn's disease (CD). Inverse variance-weighted, MR-Egger, and weighted median tests were used to assess exposure-outcome causality. The MR-Egger intercept was used to assess horizontal pleiotropy. Co-chran's Q and leave-one-out method were used to analyze heterogeneity and sensitivity, respectively.

RESULTS

Our MR analysis indicated that T1D was associated with a reduced risk of IBD [odds ratio (OR): 0.959; 95% confidence interval (CI): 0.938-0.980; P < 0.001] and UC (OR: 0.960; 95%CI: 0.929-0.992; P = 0.015), with no significant association observed in terms of CD risk (OR: 0.966; 95%CI: 0.913-1.022; P = 0.227). The MR-Egger intercept showed no horizontal pleiotropy (P > 0.05). Cochran's Q and leave-one-out sensitivity analyses showed that the results were not heterogeneous (P > 0.05) and were robust.

CONCLUSION

This MR analysis suggests that T1D serves as a potential protective factor against IBD and UC but is independent of CD.

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review

BACKGROUND

Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies.

METHODS

We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment.

RESULTS

Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation.

CONCLUSIONS

Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.

Emerging therapeutic options in the management of diabetes: recent trends, challenges and future directions

Diabetes is a serious health issue that causes a progressive dysregulation of carbohydrate metabolism due to insufficient insulin hormone, leading to consistently high blood glucose levels. According to the epidemiological data, the prevalence of diabetes has been increasing globally, affecting millions of individuals. It is a long-term condition that increases the risk of various diseases caused by damage to small and large blood vessels. There are two main subtypes of diabetes: type 1 and type 2, with type 2 being the most prevalent. Genetic and molecular studies have identified several genetic variants and metabolic pathways that contribute to the development and progression of diabetes. Current treatments include gene therapy, stem cell therapy, statin therapy, and other drugs. Moreover, recent advancements in therapeutics have also focused on developing novel drugs targeting these pathways, including incretin mimetics, SGLT2 inhibitors, and GLP-1 receptor agonists, which have shown promising results in improving glycemic control and reducing the risk of complications. However, these treatments are often expensive, inaccessible to patients in underdeveloped countries, and can have severe side effects. Peptides, such as glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), are being explored as a potential therapy for diabetes. These peptides are postprandial glucose-dependent pancreatic beta-cell insulin secretagogues and have received much attention as a possible treatment option. Despite these advances, diabetes remains a major health challenge, and further research is needed to develop effective treatments and prevent its complications. This review covers various aspects of diabetes, including epidemiology, genetic and molecular basis, and recent advancements in therapeutics including herbal and synthetic peptides.

Lessons and Gaps in the Prediction and Prevention of Type 1 Diabetes

Type 1 diabetes (T1D) is a serious chronic autoimmune condition. Even though the root cause of T1D development has yet to be determined, enough is known about the natural history of T1D pathogenesis to allow study of interventions that may delay or even prevent the onset of hyperglycemia and clinical T1D. Primary prevention aims to prevent the onset of beta cell autoimmunity in asymptomatic people at high genetic risk for T1D. Secondary prevention strategies aim to preserve functional beta cells once autoimmunity is present, and tertiary prevention aims to initiate and extend partial remission of beta cell destruction after the clinical onset of T1D. The approval of teplizumab in the United States to delay the onset of clinical T1D marks an impressive milestone in diabetes care. This treatment opens the door to a paradigm shift in T1D care. People with T1D risk need to be identified early by measuring T1D related islet autoantibodies. Identifying people with T1D before they have symptoms will facilitate better understanding of pre-symptomatic T1D progression and T1D prevention strategies that may be effective.

Non-HLA Gene Polymorphisms in the Pathogenesis of Type 1 Diabetes: Phase and Endotype Specific Effects

The non-HLA loci conferring susceptibility to type 1 diabetes determine approximately half of the genetic disease risk, and several of them have been shown to affect immune-cell or pancreatic β-cell functions. A number of these loci have shown associations with the appearance of autoantibodies or with progression from seroconversion to clinical type 1 diabetes. In the current study, we have re-analyzed 21 of our loci with prior association evidence using an expanded DIPP follow-up cohort of 976 autoantibody positive cases and 1,910 matched controls. Survival analysis using Cox regression was applied for time periods from birth to seroconversion and from seroconversion to type 1 diabetes. The appearance of autoantibodies was also analyzed in endotypes, which are defined by the first appearing autoantibody, either IAA or GADA. Analyzing the time period from birth to seroconversion, we were able to replicate our previous association findings at PTPN22, INS, and NRP1. Novel findings included associations with ERBB3, UBASH3A, PTPN2, and FUT2. In the time period from seroconversion to clinical type 1 diabetes, prior associations with PTPN2, CD226, and PTPN22 were replicated, and a novel association with STAT4 was observed. Analyzing the appearance of autoantibodies in endotypes, the PTPN22 association was specific for IAA-first. In the progression phase, STAT4 was specific for IAA-first and ERBB3 to GADA-first. In conclusion, our results further the knowledge of the function of non-HLA risk polymorphisms in detailing endotype specificity and timing of disease development.

The Multifactorial Progression from the Islet Autoimmunity to Type 1 Diabetes in Children

Type 1 Diabetes (T1D) results from autoimmune destruction of insulin producing pancreatic ß-cells. This disease, with a peak incidence in childhood, causes the lifelong need for insulin injections and necessitates careful monitoring of blood glucose levels. However, despite the current insulin therapies, it still shortens life expectancy due to complications affecting multiple organs. Recently, the incidence of T1D in childhood has increased by 3-5% per year in most developed Western countries. The heterogeneity of the disease process is supported by the findings of follow-up studies started early in infancy. The development of T1D is usually preceded by the appearance of autoantibodies targeted against antigens expressed in the pancreatic islets. The risk of T1D increases significantly with an increasing number of positive autoantibodies. The order of autoantibody appearance affects the disease risk. Genetic susceptibility, mainly defined by the human leukocyte antigen (HLA) class II gene region and environmental factors, is important in the development of islet autoimmunity and T1D. Environmental factors, mainly those linked to the changes in the gut microbiome as well as several pathogens, especially viruses, and diet are key modulators of T1D. The aim of this paper is to expand the understanding of the aetiology and pathogenesis of T1D in childhood by detailed description and comparison of factors affecting the progression from the islet autoimmunity to T1D in children.

Genetic profile considerations for induction of allogeneic chimerism as a therapeutic approach for type 1 diabetes mellitus

The major therapeutic modality for type 1 diabetes mellitus (T1DM) remains sustaining euglycemia by exogenous administration of insulin. Based on a new understanding of bone marrow structural and functional dynamics, a conditioning-free bone marrow transplantation (BMT), with reduced adverse effects, opens the possibility for evaluating β cell regeneration and restoration of euglycemia by induction of allogeneic chimerism in patients T1DM, as shown in a mouse model. With this therapeutic modality, donor bone marrow (BM) selection based on T1DM-predisposing and preventive phenotypes will improve treatment outcomes by limiting the risk of exacerbating the autoimmune processes in the BM recipient.

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.

Immune Mechanisms and Pathways Targeted in Type 1 Diabetes

PURPOSE OF REVIEW

The immunosuppressive agent cyclosporine was first reported to lower daily insulin dose and improve glycemic control in patients with new-onset type 1 diabetes (T1D) in 1984. While renal toxicity limited cyclosporine's extended use, this observation ignited collaborative efforts to identify immunotherapeutic agents capable of safely preserving β cells in patients with or at risk for T1D.

RECENT FINDINGS

Advances in T1D prediction and early diagnosis, together with expanded knowledge of the disease mechanisms, have facilitated trials targeting specific immune cell subsets, autoantigens, and pathways. In addition, clinical responder and non-responder subsets have been defined through the use of metabolic and immunological readouts. Herein, we review emerging T1D biomarkers within the context of recent and ongoing T1D immunotherapy trials. We also discuss responder/non-responder analyses in an effort to identify therapeutic mechanisms, define actionable pathways, and guide subject selection, drug dosing, and tailored combination drug therapy for future T1D trials.

Prediction of type 1 diabetes using a genetic risk model in the Diabetes Autoimmunity Study in the Young

BACKGROUND

Genetic predisposition for type 1 diabetes (T1D) is largely determined by human leukocyte antigen (HLA) genes; however, over 50 other genetic regions confer susceptibility. We evaluated a previously reported 10-factor weighted model derived from the Type 1 Diabetes Genetics Consortium to predict the development of diabetes in the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort. Performance of the model, derived from individuals with first-degree relatives (FDR) with T1D, was evaluated in DAISY general population (GP) participants as well as FDR subjects.

METHODS

The 10-factor weighted risk model (HLA, PTPN22 , INS , IL2RA , ERBB3 , ORMDL3 , BACH2 , IL27 , GLIS3 , RNLS ), 3-factor model (HLA, PTPN22, INS ), and HLA alone were compared for the prediction of diabetes in children with complete SNP data (n = 1941).

RESULTS

Stratification by risk score significantly predicted progression to diabetes by Kaplan-Meier analysis (GP: P = .00006; FDR: P = .0022). The 10-factor model performed better in discriminating diabetes outcome than HLA alone (GP, P = .03; FDR, P = .01). In GP, the restricted 3-factor model was superior to HLA (P = .03), but not different from the 10-factor model (P = .22). In contrast, for FDR the 3-factor model did not show improvement over HLA (P = .12) and performed worse than the 10-factor model (P = .02) CONCLUSIONS: We have shown a 10-factor risk model predicts development of diabetes in both GP and FDR children. While this model was superior to a minimal model in FDR, it did not confer improvement in GP. Differences in model performance in FDR vs GP children may lead to important insights into screening strategies specific to these groups.

The Influence of Type 1 Diabetes Genetic Susceptibility Regions, Age, Sex, and Family History on the Progression From Multiple Autoantibodies to Type 1 Diabetes: A TEDDY Study Report

This article seeks to determine whether factors related to autoimmunity risk remain significant after the initiation of two or more diabetes-related autoantibodies and continue to contribute to type 1 diabetes (T1D) risk among autoantibody-positive children in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Characteristics included are age at multiple autoantibody positivity, sex, selected high-risk HLA-DR-DQ genotypes, relationship to a family member with T1D, autoantibody at seroconversion, INS gene (rs1004446_A), and non-HLA gene polymorphisms identified by the Type 1 Diabetes Genetics Consortium (T1DGC). The risk of progression to T1D was not different among those with or without a family history of T1D (P = 0.39) or HLA-DR-DQ genotypes (P = 0.74). Age at developing multiple autoantibodies (hazard ratio = 0.96 per 1-month increase in age; 95% CI 0.95, 0.97; P < 0.001) and the type of first autoantibody (when more than a single autoantibody was the first-appearing indication of seroconversion [P = 0.006]) were statistically significant. Female sex was also a significant risk factor (P = 0.03). Three single nucleotide polymorphisms were associated with increased diabetes risk (rs10517086_A [P = 0.03], rs1534422_G [P = 0.006], and rs2327832_G [P = 0.03] in TNFAIP3) and one with decreased risk (rs1004446_A in INS [P = 0.006]). The TEDDY data suggest that non-HLA gene polymorphisms may play a different role in the initiation of autoimmunity than they do in progression to T1D once autoimmunity has appeared. The strength of these associations may be related to the age of the population and the high-risk HLA-DR-DQ subtypes studied.

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.

PTPN22 and islet-specific autoimmunity: What have the mouse models taught us?

An allelic variant of the protein tyrosin phosphatase non-receptor 22 (PTPN22) gene, PTPN22 R620W, constitutes the strongest non-HLA genetic risk factor for the development of type 1 diabetes (T1D). A number of studies using mouse models have addressed how PTPN22 predisposes to T1D. PTPN22 downmodulation, overexpression or expression of the variant gene in genetically manipulated mice has generated controversial results. These discrepancies probably derive from the fact that PTPN22 has differential effects on innate and adaptive immune responses. Moreover, the effects of PTPN22 are dependent on other genetic variables. Here we discuss these findings and try to explain the discrepancies. Exploring the mechanism by which PTPN22 contributes to islet-specific autoimmunity could help us understand its role in T1D pathogenesis and exploit it as a potential therapeutic target to prevent the disease.

Non-HLA type 1 diabetes genes modulate disease risk together with HLA-DQ and islet autoantibodies

The possible interrelations between HLA-DQ, non-HLA single nucleotide polymorphisms (SNPs) and islet autoantibodies were investigated at clinical onset in 1-34 year old type 1 diabetes (T1D) patients (n=305) and controls (n=203). Among the non-HLA SNPs reported by the Type 1 Diabetes Genetics Consortium, 24% were supported in this Swedish replication set including that the increased risk of minor PTPN22 allele and high risk HLA was modified by GAD65 autoantibodies. The association between T1D and the minor AA+AC genotype in ERBB3 gene was stronger among IA-2 autoantibody-positive patients (comparison p=0.047). The association between T1D and the common insulin (AA) genotype was stronger among insulin autoantibody (IAA)-positive patients (comparison p=0.008). In contrast, the association between T1D and unidentified 26471 gene was stronger among IAA-negative (comparison p=0.049) and IA-2 autoantibody-negative (comparison p=0.052) patients. Finally, the association between IL2RA and T1D was stronger among IAA-positive than among IAA-negative patients (comparison p=0.028). These results suggest that the increased risk of T1D by non-HLA genes is often modified by both islet autoantibodies and HLA-DQ. The interactions between non-HLA genes, islet autoantibodies and HLA-DQ should be taken into account in T1D prediction studies as well as in prevention trials aimed at inducing immunological tolerance to islet autoantigens.

Non-HLA gene effects on the disease process of type 1 diabetes: From HLA susceptibility to overt disease

In addition to the HLA region numerous other gene loci have shown association with type 1 diabetes. How these polymorphisms exert their function has not been comprehensively described, however. We assessed the effect of 39 single nucleotide polymorphisms (SNP) on the development of autoantibody positivity, on progression from autoantibody positivity to clinical disease and on the specificity of the antibody initiating the autoimmune process in 521 autoantibody-positive and 989 control children from a follow-up study starting from birth. Interestingly, PTPN2 rs45450798 gene polymorphism was observed to strongly affect the progression rate of beta-cell destruction after the appearance of humoral beta-cell autoimmunity. Moreover, primary autoantigen dependent associations were also observed as effect of the IKZF4-ERBB3 region on the progression rate of β-cell destruction was restricted to children with GAD antibodies as their first autoantibody whereas the effect of the INS rs 689 polymorphism was observed among subjects with insulin as the primary autoantigen. In the whole study cohort, INS rs689, PTPN22 rs2476601 and IFIH1 rs1990760 polymorphisms were associated with the appearance of beta-cell autoantibodies. These findings provide new insights into the role of genetic factors implicated in the pathogenesis of type 1 diabetes. The effect of some of the gene variants is restricted to control the initiation of β-cell autoimmunity whereas others modify the destruction rate of the β-cells. Furthermore, signs of primary autoantigen-related pathways were detected.

Role of Type 1 Diabetes-Associated SNPs on Risk of Autoantibody Positivity in the TEDDY Study

The Environmental Determinants of Diabetes in the Young (TEDDY) study prospectively follows 8,677 children enrolled from birth who carry HLA-susceptibility genotypes for development of islet autoantibodies (IA) and type 1 diabetes (T1D). During the median follow-up time of 57 months, 350 children developed at least one persistent IA (GAD antibody, IA-2A, or micro insulin autoantibodies) and 84 of them progressed to T1D. We genotyped 5,164 Caucasian children for 41 non-HLA single nucleotide polymorphisms (SNPs) that achieved genome-wide significance for association with T1D in the genome-wide association scan meta-analysis conducted by the Type 1 Diabetes Genetics Consortium. In TEDDY participants carrying high-risk HLA genotypes, eight SNPs achieved significant association to development of IA using time-to-event analysis (P < 0.05), whereof four were significant after adjustment for multiple testing (P < 0.0012): rs2476601 in PTPN22 (hazard ratio [HR] 1.54 [95% CI 1.27-1.88]), rs2292239 in ERBB3 (HR 1.33 [95% CI 1.14-1.55]), rs3184504 in SH2B3 (HR 1.38 [95% CI 1.19-1.61]), and rs1004446 in INS (HR 0.77 [0.66-0.90]). These SNPs were also significantly associated with T1D in particular: rs2476601 (HR 2.42 [95% CI 1.70-3.44]). Although genes in the HLA region remain the most important genetic risk factors for T1D, other non-HLA genetic factors contribute to IA, a first step in the pathogenesis of T1D, and the progression of the disease.

Risk of type 1 diabetes progression in islet autoantibody-positive children can be further stratified using expression patterns of multiple genes implicated in peripheral blood lymphocyte activation and function

There is tremendous scientific and clinical value to further improving the predictive power of autoantibodies because autoantibody-positive (AbP) children have heterogeneous rates of progression to clinical diabetes. This study explored the potential of gene expression profiles as biomarkers for risk stratification among 104 AbP subjects from the Diabetes Autoimmunity Study in the Young (DAISY) using a discovery data set based on microarray and a validation data set based on real-time RT-PCR. The microarray data identified 454 candidate genes with expression levels associated with various type 1 diabetes (T1D) progression rates. RT-PCR analyses of the top-27 candidate genes confirmed 5 genes (BACH2, IGLL3, EIF3A, CDC20, and TXNDC5) associated with differential progression and implicated in lymphocyte activation and function. Multivariate analyses of these five genes in the discovery and validation data sets identified and confirmed four multigene models (BI, ICE, BICE, and BITE, with each letter representing a gene) that consistently stratify high- and low-risk subsets of AbP subjects with hazard ratios >6 (P < 0.01). The results suggest that these genes may be involved in T1D pathogenesis and potentially serve as excellent gene expression biomarkers to predict the risk of progression to clinical diabetes for AbP subjects.

A strategy to find gene combinations that identify children who progress rapidly to type 1 diabetes after islet autoantibody seroconversion

We recently developed a novel approach capable of identifying gene combinations to obtain maximal disease risk stratification. Type 1 diabetes has a preclinical phase including seroconversion to autoimmunity and subsequent progression to diabetes. Here, we applied our gene combination approach to identify combinations that contribute either to islet autoimmunity or to the progression from islet autoantibodies to diabetes onset. We examined 12 type 1 diabetes susceptibility genes (INS, ERBB3, PTPN2, IFIH1, PTPN22, KIAA0350, CD25, CTLA4, SH2B3, IL2, IL18RAP, IL10) in a cohort of children of parents with type 1 diabetes and prospectively followed from birth. The most predictive combination was subsequently applied to a smaller validation cohort. The combinations of genes only marginally contributed to the risk of developing islet autoimmunity, but could substantially modify risk of progression to diabetes in islet autoantibody-positive children. The greatest discrimination was provided by risk allele scores of five genes, INS, IFIH1, IL18RAP, CD25, and IL2 genes, which could identify 80 % of islet autoantibody-positive children who progressed to diabetes within 6 years of seroconversion and discriminate high risk (63 % within 6 years; 95 % CI 45-81 %) and low risk (11 % within 6 years; 95 % CI 0.1-22 %; p = 4 × 10(-5)) antibody-positive children. Risk stratification by these five genes was confirmed in a second cohort of islet autoantibody children. These findings highlight genes that may affect the rate of the beta-cell destruction process once autoimmunity has initiated and may help to identify islet autoantibody-positive subjects with rapid progression to diabetes.

Tyrosine phosphatase PTPN22: multifunctional regulator of immune signaling, development, and disease

Inheritance of a coding variant of the protein tyrosine phosphatase nonreceptor type 22 (PTPN22) gene is associated with increased susceptibility to autoimmunity and infection. Efforts to elucidate the mechanisms by which the PTPN22-C1858T variant modulates disease risk revealed that PTPN22 performs a signaling function in multiple biochemical pathways and cell types. Capable of both enzymatic activity and adaptor functions, PTPN22 modulates signaling through antigen and innate immune receptors. PTPN22 plays roles in lymphocyte development and activation, establishment of tolerance, and innate immune cell-mediated host defense and immunoregulation. The disease-associated PTPN22-R620W variant protein is likely involved in multiple stages of the pathogenesis of autoimmunity. Establishment of a tolerant B cell repertoire is disrupted by PTPN22-R620W action during immature B cell selection, and PTPN22-R620W alters mature T cell responsiveness. However, after autoimmune attack has initiated tissue injury, PTPN22-R620W may foster inflammation through modulating the balance of myeloid cell-produced cytokines.

Pathogenesis of type 1 diabetes: lessons from natural history studies of high-risk individuals

Type 1 diabetes (T1D) is an autoimmune disease characterized by known genetic risk factors with T cell-mediated infiltration and destruction of the beta cells within pancreatic islets. Autoantibodies are the most significant preclinical marker of T1D, and birth cohort studies have provided important insights into the natural history of autoimmunity and T1D. While HLA remains the strongest genetic risk factor, a number of novel gene variants associated with T1D have been found through genome-wide studies, some of which have been linked to suspected environmental risk factors. Multiple environmental factors that have been suggested to play a role in the development of T1D await confirmation. Current risk-stratification models for T1D take into account genetic risk factors and autoantibodies. In the future, metabolic profiles, epigenetics, as well as environmental risk factors may be included in such models.

Protein tyrosine phosphatases and type 1 diabetes: genetic and functional implications of PTPN2 and PTPN22

Protein tyrosine phosphatases (PTPs) play a central role in modulating the transduction of cellular signals, including the cells of the immune system. Several PTPs, PTPN22, PTPN2, and UBASH3A, have been associated with risk of type 1 diabetes (T1D) by genome wide association studies. Based on the current understanding of PTPs, it is clear that these variants impact antigen receptor signaling and cytokine signaling. This impact likely contributes to the development and progression of autoimmunity through multiple mechanisms, including failures of central and peripheral tolerance and the promotion of proinflammatory T cell responses. In this review, we discuss the genetic and functional implications of two of these PTPs, PTPN22 and PTPN2, in the development of T1D. We describe the known roles of these proteins in immune function, and how the expression and function of these proteins is altered by the genetic variants associated with T1D. Yet, there are still controversies in the field that require further study and the development of new approaches to extend our understanding of these PTP variants, with the goal of using the information gained to improve our ability to predict and cure T1D.

Influence of type 1 diabetes genes on disease progression: similarities and differences between countries

Type 1 diabetes (T1D) is an autoimmune disease causing the destruction of pancreatic beta cells. The onset of clinical T1D is preceded by a time period called pre-diabetes, the duration of which varies widely. However, not all subjects developing beta-cell autoimmunity progress to clinical T1D. The inherited risk for T1D is determined by the human leukocyte antigen (HLA) class II genes, HLA class I genes, and several loci outside the HLA area. Although the role of the genetic risk variants in disease pathogenesis is not completely understood, some of the variants affecting disease risk are thought to influence the initiation of beta-cell autoimmunity whereas others seem to play a role during the later stages of the autoimmune process. In this review we describe the current knowledge on the genetic factors mediating the fate of already-established beta-cell autoimmunity and the rate of beta-cell destruction.

A strategy for combining minor genetic susceptibility genes to improve prediction of disease in type 1 diabetes

Genome-wide association studies have identified gene regions associated with type 1 diabetes. The aim of this study was to determine how the combined allele frequency of multiple susceptibility genes can stratify islet autoimmunity and/or type 1 diabetes risk. Children of parents with type 1 diabetes and prospectively followed from birth for the development of islet autoantibodies and diabetes were genotyped for single-nucleotide polymorphisms at 12 type 1 diabetes susceptibility genes (ERBB3, PTPN2, IFIH1, PTPN22, KIAA0350, CD25, CTLA4, SH2B3, IL2, IL18RAP, IL10 and COBL). Non-human leukocyte antigen (HLA) risk score was defined by the total number of risk alleles at these genes. Receiver operator curve analysis showed that the non-HLA gene combinations were highly effective in discriminating diabetes and most effective in children with a high-risk HLA genotype. The greatest diabetes discrimination was obtained by the sum of risk alleles for eight genes (IFIH1, CTLA4, PTPN22, IL18RAP, SH2B3, KIAA0350, COBL and ERBB3) in the HLA-risk children. Non-HLA-risk allele scores stratified risk for developing islet autoantibodies and diabetes, and progression from islet autoimmunity to diabetes. Genotyping at multiple susceptibility loci in children from affected families can identify neonates with sufficient genetic risk of type 1 diabetes to be considered for early intervention.