Genetic variation at ERBB3/IKZF4 and sexual dimorphism in epitope spreading in single autoantibody-positive relatives

IKZF4 acts as a novel tumor suppressor in non-small cell lung cancer by suppressing Notch signaling pathway

Non-small cell lung cancer (NSCLC) is the predominant cause of cancer-related mortality globally, although many clinical efforts have been developed to improve the outcomes. The Ikaros zing-finger family transcription factors (IKZFs) have been proved to play pivotal roles in lymphopoiesis and myeloma progression, but their roles in solid tumors development remain unclear. We performed integrative bioinformatical analysis to determine the dysregulation expression of IKZFs in multiple tumors and the correlation between IKZF4 and NSCLC tumor environment. We showed that IKZFs were dysregulated in multiple tumors and IKZF4 was significantly decreased in NSCLC tissues and cell lines due to promoter hypermethylation. We found that low IKZF4 expression obviously correlated with patients' poor clinical outcome. We revealed that IKZF4 overexpression inhibited NSCLC cell growth, migration and xenograft tumor growth, supporting the inhibitory role of IKZF4 in NSCLC tumorigenesis. Additionally, integrative bioinformatical analysis showed that IKZF4 was involved in NSCLC tumor microenvironment. Mechanically, RNA-seq results showed that IKZF4 forced-expression remarkably suppressed Notch signaling pathway in NSCLC, which was validated by qRT-PCR and immunoblot assays. Moreover, we screened several potential agonists for IKZF4.

CTLA4, SH2B3, and CLEC16A diversely affect the progression of early islet autoimmunity in relatives of Type 1 diabetes patients

The HLA region is the major genetic risk determinant of Type 1 diabetes. How non-HLA loci contribute to the genetic risk is incompletely understood, but there are indications that at least some impact progression of asymptomatic autoimmunity. We examined whether SNPs in 7 susceptibility loci (INS, SH2B3, PTPN2, PTPN22, CTLA4, CLEC16A, and IL2RA) could improve prediction of the progression from single to multiple autoantibody positivity, and from there on to diagnosis. SNPs were genotyped in persistently autoantibody positive relatives by allelic discrimination qPCR and disease progression was studied by multivariate Cox regression analysis. In our cohort, only the CTLA4 GA genotype (rs3087243, P = 0.002) and the CLEC16A AA genotype (rs12708716, P = 0.021) were associated with accelerated progression from single to multiple autoantibody positivity, but their effects were restricted to presence of HLA-DQ2/DQ8, and IAA as first autoantibody, respectively. The interaction of CTLA4 and HLA-DQ2/DQ8 overruled the effect of DQ2/DQ8 alone. The HLA-DQ2/DQ8-mediated risk of progression to multiple autoantibodies nearly entirely depended on heterozygosity for CTLA4. The SH2B3 TT genotype (rs3184504) was protective for HLA-DQ8 positive subjects (P = 0.003). At the stage of multiple autoantibodies, only the CTLA4 GA genotype was a minor independent risk factor for progression towards clinical diabetes (P = 0.034). Our study shows that non-HLA polymorphisms impact progression of islet autoimmunity in a subgroup-, stage- and SNP-specific way, suggesting distinct mechanisms. If confirmed, these findings may help refine risk assessment, follow-up, and prevention trials in risk groups.

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.

Pathogenesis of Type 1 Diabetes: Established Facts and New Insights

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