From markers to molecular mechanisms: type 1 diabetes in the post-GWAS era

Shared genetic architecture between autoimmune disorders and B-cell acute lymphoblastic leukemia: insights from large-scale genome-wide cross-trait analysis

BACKGROUND

To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved.

METHODS

Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations.

RESULTS

Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P < 5 × 10-8), 16 of which had strong evidence of colocalization. We demonstrated that several loci have been previously reported (e.g., 17q21) and discovered some novel loci (e.g., 10p12, 5p13). Further gene-level identified 194 unique pleiotropic genes, for example IKZF1, GATA3, IKZF3, GSDMB, and ORMDL3. Pathway analysis determined the key role of cellular response to cytokine stimulus, B cell activation, and JAK-STAT signaling pathways. SNP-level and gene-level tissue enrichment suggested that crucial role pleiotropic mechanisms involved in the spleen, whole blood, and EBV-transformed lymphocytes. Also, hyprcoloc and stratified LD score regression analyses revealed that B cells at different developmental stages may be involved in mechanisms shared between two different diseases. Finally, two-sample MR analysis determined causal effects of asthma and rheumatoid arthritis on B-ALL.

CONCLUSIONS

Our research proved shared genetic architecture between autoimmune disorders and B-ALL and shed light on the potential mechanism that might involve in.

Environmental Triggering of Type 1 Diabetes Autoimmunity

Type 1 diabetes (T1D) is a chronic autoimmune disease in which pancreatic islet β cells are destroyed by immune cells, ultimately leading to overt diabetes. The progressive increase in T1D incidence over the years points to the role of environmental factors in triggering or accelerating the disease process which develops on a highly multigenic susceptibility background. Evidence that environmental factors induce T1D has mostly been obtained in animal models. In the human, associations between viruses, dietary habits or changes in the microbiota and the development of islet cell autoantibodies or overt diabetes have been reported. So far, prediction of T1D development is mostly based on autoantibody detection. Future work should focus on identifying a causality between the different environmental risk factors and T1D development to improve prediction scores. This should allow developing preventive strategies to limit the T1D burden in the future.

Biomarkers of Checkpoint Inhibitor Induced Immune-Related Adverse Events-A Comprehensive Review

Immune checkpoint inhibitors (ICIs) have substantially improved the prognosis of patients with different types of cancer. Through blockade of cytotoxic T-lymphocyte antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1), negative feedback mechanisms of the immune system are inhibited, potentially resulting in very durable anti-tumor responses. Despite their promise, ICIs can also elicit auto-immune toxicities. These immune-related adverse events (irAEs) can be severe and sometimes even fatal. Therefore, being able to predict severe irAEs in patients would be of added value in clinical decision making. A search was performed using “adverse events”, “immune checkpoint inhibitor”, “biomarker”, and synonyms in PubMed, yielding 3580 search results. After screening title and abstract on the relevance to the review question, statistical significance of reported potential biomarkers, and evaluation of the remaining full papers, 35 articles were included. Five additional reports were obtained by means of citations and by using the similar article function on PubMed. The current knowledge is presented in comprehensive tables summarizing blood-based, immunogenetic and microbial biomarkers predicting irAEs prior to and during ICI therapy. Until now, no single biomarker has proven to be sufficiently predictive for irAE development. Recommendations for further research on this topic are presented.

Type 1 diabetes: genes associated with disease development

Type 1 diabetes (T1D) is the third most common autoimmune disease which develops due to genetic and environmental risk factors. Based on the World Health Organization (WHO) report from 2014 the number of people suffering from all types of diabetes ascended to 422 million, compared to 108 million in 1980. It was calculated that this number will double by the end of 2030. In 2015 American Diabetes Association (ADA) announced that 30.3 million Americans (that is 9.4% of the overall population) had diabetes of which only approximately 1.25 million had T1D. Nowadays, T1D represents roughly 10% of adult diabetes cases total. Multiple genetic abnormalities at different loci have been found to contribute to type 1 diabetes development. The analysis of genome-wide association studies (GWAS) of T1D has identified over 50 susceptible regions (and genes within these regions). Many of these regions are defined by single nucleotide polymorphisms (SNPs) but molecular mechanisms through which they increase or lower the risk of diabetes remain unknown. Genetic factors (in existence since birth) can be detected long before the emergence of immunological or clinical markers. Therefore, a comprehensive understanding of the multiple genetic factors underlying T1D is extremely important for further clinical trials and development of personalized medicine for diabetic patients. We present an overview of current studies and information about regions in the human genome associated with T1D. Moreover, we also put forward information about epigenetic modifications, non-coding RNAs and environmental factors involved in T1D development and onset.

Using Genetic Risk Score Approaches to Infer Whether an Environmental Factor Attenuates or Exacerbates the Adverse Influence of a Candidate Gene

Some candidate genes have been robustly reported to be associated with complex traits, such as the fat mass and obesity-associated (FTO) gene on body mass index (BMI), and the fibroblast growth factor 5 (FGF5) gene on blood pressure levels. It is of interest to know whether an environmental factor (E) can attenuate or exacerbate the adverse influence of a candidate gene. To this end, we here evaluate the performance of “genetic risk score” (GRS) approaches to detect “gene-environment interactions” (G × E). In the first stage, a GRS is calculated according to the genotypes of variants in a candidate gene. In the second stage, we test whether E can significantly modify this GRS effect. This two-stage procedure can not only provide a p-value for a G × E test but also guide inferences on how E modifies the adverse effect of a gene. With systematic simulations, we compared several ways to construct a GRS. If E exacerbates the adverse influence of a gene, GRS formed by the elastic net (ENET) or the least absolute shrinkage and selection operator (LASSO) is recommended. However, the performance of ENET or LASSO will be compromised if E attenuates the adverse influence of a gene, and using the ridge regression (RIDGE) can be more powerful in this situation. Applying RIDGE to 18,424 subjects in the Taiwan Biobank, we showed that performing regular exercise can attenuate the adverse influence of the FTO gene on four obesity measures: BMI (p = 0.0009), body fat percentage (p = 0.0031), waist circumference (p = 0.0052), and hip circumference (p = 0.0001). As another example, we used RIDGE and found the FGF5 gene has a stronger effect on blood pressure in Han Chinese with a higher waist-to-hip ratio [p = 0.0013 for diastolic blood pressure (DBP) and p = 0.0027 for systolic blood pressure (SBP)]. This study provides an evaluation on the GRS approaches, which is important to infer whether E attenuates or exacerbates the adverse influence of a candidate gene.

Genes predisposing to type 1 diabetes mellitus and pathophysiology: a narrative review

The possibility of targeting the causal genes along with the mechanisms of pathogenically complex diseases has led to numerous studies on the genetic etiology of some diseases. In particular, studies have added more genes to the list of type 1 diabetes mellitus (T1DM) suspect genes, necessitating an update for the interest of all stakeholders. Therefore this review articulates T1DM suspect genes and their pathophysiology. Notable electronic databases, including Medline, Scopus, PubMed, and Google-Scholar were searched for relevant information. The search identified over 73 genes suspected in the pathogenesis of T1DM, with human leukocyte antigen, insulin gene, and cytotoxic T lymphocyte-associated antigen 4 accounting for most of the cases. Mutations in these genes, along with environmental factors, may produce a defective immune response in the pancreas, resulting in β-cell autoimmunity, insulin deficiency, and hyperglycemia. The mechanisms leading to these cellular reactions are gene-specific and, if targeted in diabetic individuals, may lead to improved treatment. Medical practitioners are advised to formulate treatment procedures that target these genes in patients with T1DM.

The challenge of modulating β-cell autoimmunity in type 1 diabetes

With the conceptual advance about four decades ago that type 1 diabetes represents an autoimmune disease, hope arose that immune-based therapies would soon emerge to prevent and reverse the disorder. However, despite dozens of clinical trials seeking to achieve these goals, the promise remains unfulfilled, at least in a pragmatic form. With the benefit of hindsight, several important reasons are likely to account for this disappointing outcome, including failure to appreciate disease heterogeneity, inappropriate use of rodent models of disease, inadequacies in addressing the immunological and metabolic contributions to the disease, suboptimal trial designs, and lack of a clear understanding of the pathogenesis of type 1 diabetes. In this Series paper, we convey how recent knowledge gains in these areas, combined with efforts related to disease staging and emerging mechanistic data from clinical trials, provide cautious optimism that immune-based approaches to prevent the loss of β cells in type 1 diabetes will emerge into clinical practice.

Avidity and Bystander Suppressive Capacity of Human Regulatory T Cells Expressing De Novo Autoreactive T-Cell Receptors in Type 1 Diabetes

The ability to alter antigen specificity by T-cell receptor (TCR) or chimeric antigen receptor (CAR) gene transfer has facilitated personalized cellular immune therapies in cancer. Inversely, this approach can be harnessed in autoimmune settings to attenuate inflammation by redirecting the specificity of regulatory T cells (Tregs). Herein, we demonstrate efficient protocols for lentiviral gene transfer of TCRs that recognize type 1 diabetes-related autoantigens with the goal of tissue-targeted induction of antigen-specific tolerance to halt β-cell destruction. We generated human Tregs expressing a high-affinity GAD_555–567-reactive TCR (clone R164), as well as the lower affinity clone 4.13 specific for the same peptide. We demonstrated that de novo Treg avatars potently suppress antigen-specific and bystander responder T-cell (Tresp) proliferation in vitro in a process that requires Treg activation (P < 0.001 versus unactivated Tregs). When Tresp were also glutamic acid decarboxylase (GAD)-reactive, the high-affinity R164 Tregs exhibited increased suppression (P < 0.01) with lower Tresp-division index (P < 0.01) than the lower affinity 4.13 Tregs. These data demonstrate the feasibility of rapid expansion of antigen-specific Tregs for applications in attenuating β-cell autoimmunity and emphasize further opportunities for engineering cellular specificities, affinities, and phenotypes to tailor Treg activity in adoptive cell therapies for the treatment of type 1 diabetes.

Association between telomere length and diabetes mellitus: A meta-analysis

Objective We investigated the relationship between diabetes and telomere length by meta-analysis. Methods We searched five popular databases for articles published between 1990 and 2015 using "diabetes" and "telomere" as search terms. Data were processed with RevMan5, and random- or fixed-effects meta-analysis was applied. The effects of geographical region, diabetes type, body mass index (BMI), age and sex were examined. Funnel plots were applied to evaluate publication bias. Results Seventeen articles were obtained from 571 references. We identified a significant association between telomere length and diabetes mellitus (standardized mean difference [SMD]: -3.41; 95% confidence interval [CI]: -4.01, -2.80; heterogeneity, I2 = 99%) by comparing 5575 patients with diabetes and 6349 healthy individuals. The pooled SMD by geographic region indicated a significant association between shortened telomere length and diabetes mellitus (SMD: -3.41; 95% CI: -4.01, -2.80; heterogeneity, I2 = 99%). In addition, telomere length was significantly associated with age (SMD: -3.41; 95% CI: -4.01, -2.80), diabetes type (SMD: -3.41; 95% CI: -4.01, -2.80), BMI (SMD: -1.61; 95% CI: -1.98, -1.23) and sex (SMD: -4.94; 95% CI: -9.47, -0.40). Conclusions The study demonstrated a close relationship between diabetes mellitus and telomere length, which was influenced by region, age, diabetes type, BMI and sex.

Genetic variations in the PSMA3, PSMA6 and PSMC6 genes are associated with type 1 diabetes in Latvians and with expression level of number of UPS-related and T1DM-susceptible genes in HapMap individuals

The ubiquitin-proteasome system (UPS), a key player of proteostasis network in the body, was implicated in type 1 diabetes mellitus (T1DM) pathogenesis. Polymorphisms in genes encoding proteasome subunits may potentially affect system efficiency. However, data in this field are still limited. To fulfil this gap, single nucleotide polymorphisms in the PSMB5 (rs11543947), PSMA6 (rs2277460, rs1048990), PSMC6 (rs2295826, rs2295827) and PSMA3 (rs2348071) genes were genotyped on susceptibility to T1DM in Latvians. The rs11543947 was found to be neutral and other loci manifested disease susceptibility, with rs1048990 and rs2348071 being the most significantly associated (P < 0.001; OR 2.042 [1.376-3.032] and OR 2.096 [1.415-3.107], respectively). Risk effect was associated with female phenotype for rs2277460 and family history for rs2277460, rs2295826 and rs2295827. Five-locus genotypes being at risk simultaneously at any two or more loci showed strong (P < 0.0001) T1DM association. The T1DM protective effects (P < 0.001) were shown for five-locus genotype and haplotype homozygous on common alleles and composed of common alleles, respectively. Using SNPexp data set, correlations have been revealed between the rs1048990, rs2295826, rs2295827 and rs2348071 T1DM risk genotypes and expression levels of 14 genes related to the UPS and 42 T1DM-susceptible genes encoding proteins involved in innate and adaptive immunity, antiviral response, insulin signalling, glucose-energy metabolism and other pathways implicated in T1DM pathogenesis. Genotype-phenotype and genotype-genotype clusterings support genotyping results. Our results provide evidence on new T1DM-susceptible loci in the PSMA3, PSMA6 and PSMC6 proteasome genes and give a new insight into the T1DM pathogenesis.