Genetic variation can modulate gene expression, and thereby phenotypic variation and susceptibility to complex diseases such as type 2 diabetes (T2D). Here we harnessed the potential of DNA and RNA sequencing in human pancreatic islets from 89 deceased donors to identify genes of potential importance in the pathogenesis of T2D. We present a catalog of genetic variants regulating gene expression (eQTL) and exon use (sQTL), including many long noncoding RNAs, which are enriched in known T2D-associated loci. Of 35 eQTL genes, whose expression differed between normoglycemic and hyperglycemic individuals, siRNA of tetraspanin 33 (TSPAN33), 5′-nucleotidase, ecto (NT5E), transmembrane emp24 protein transport domain containing 6 (TMED6), and p21 protein activated kinase 7 (PAK7) in INS1 cells resulted in reduced glucose-stimulated insulin secretion. In addition, we provide a genome-wide catalog of allelic expression imbalance, which is also enriched in known T2D-associated loci. Notably, allelic imbalance in paternally expressed gene 3 (PEG3) was associated with its promoter methylation and T2D status. Finally, RNA editing events were less common in islets than previously suggested in other tissues. Taken together, this study provides new insights into the complexity of gene regulation in human pancreatic islets and better understanding of how genetic variation can influence glucose metabolism.T ype 2 diabetes (T2D) is an increasing global health problem (1). Although genome-wide association studies (GWAS) have yielded more than 70 loci associated with T2D or related traits (2, 3), they have not provided the expected breakthrough in our understanding of the pathogenesis of the disease. They have nonetheless pointed at a central role of the pancreatic islets and β-cell dysfunction in the development of the disease (4, 5). It therefore seems pertinent to focus on human pancreatic islets to obtain insights into the molecular mechanisms causing the disease (6, 7). Given that most SNPs associated with T2D lie in noncoding regions, the majority of causal variants are likely to regulate gene expression rather than protein function per se. Therefore, combination of DNA and RNA sequencing in the same individuals may help to disentangle the role these SNPs play in the pathogenesis of the disease (8). Although the human pancreatic islet transcriptome has been previously described (6, 9-18), using microarrays or RNA sequencing of a limited number of nondiabetic individuals, this has not allowed a more global analysis of the complexity of the islet transcriptome in T2D. Here we combined genotypic imputation, expression microarrays, and exome and RNA sequencing (ExomeSeq and RNA-Seq) in a large number of human pancreatic islets from deceased donors with and without T2D. This study identified a number of novel genes, including long intergenic noncoding RNAs (lincRNAs), whose expression and/or splicing influences insulin secretion and is associated with glycemia. In addition, we provide a catalog of RNA editing and allele-specific expr...

IntroductionTransforming growth factor beta (TGF-␤) is recognized as a highly pleiotropic family of growth factors involved in the regulation of numerous physiologic processes including development, hematopoiesis, wound healing, and immune response. The 3 isoforms of this growth factor that have been identified in mammals (TGF-␤1, -␤2, and -␤3) are encoded by distinct genetic loci and share a high level of homology. They act on virtually all cell types and mediate similar cellular responses in vitro, like regulation of proliferation, differentiation, apoptosis, and extracellular matrix synthesis. [1][2][3] In vivo, however, they demonstrate partly unique sets of physiologic functions due to different tissue distribution and temporal expression during development. [4][5][6] The TGF-␤ isoforms exert all their cellular functions through formation of a tetrameric complex with the 2 cell surface receptors T␤RI and T␤RII. Complex formation leads to phosphorylation of T␤RI on serine/threonine residues and propagation of the intracellular signal to the nucleus through a chain of phosphorylations of Smads, which regulate gene expression in cooperation with other transcription factors. 7 A growing body of evidence suggests TGF-␤ to be one of the major regulators of immune function, acting both by suppressive and stimulatory mechanisms on leukocytes to achieve a balanced immune response. [8][9][10] The suppressive mode of action has been highlighted by studies demonstrating inhibition of interleukin 1 (IL-1)-, IL-2-, and IL-7-dependent thymocyte proliferation by TGF-␤ 11-16 through autocrine and paracrine mechanisms, 13,17,18 whereas immunostimulatory functions were suggested by the capacity of TGF-␤ to induce cytokine expression in T cells and to promote effector expansion by inhibition of apoptosis. [19][20][21] Moreover, the influence of TGF-␤ on the development and function of other cells of the immune system, such as B cells, macrophages, and dendritic cells, has been reported. 10 Striking evidence for the importance of TGF-␤ in immune regulation was reported from studies on TGF-␤-null animals that demonstrated postnatal lethality and massive multifocal inflammation affecting multiple organs. 9,22,23 The uncontrolled inflammatory reaction has been ascribed to autoimmune mechanisms including autoantibodies and autoreactive T cells. [24][25][26][27] However, attempts to develop the phenotype by transplanting TGF-␤1-null bone marrow to healthy recipient mice unexpectedly resulted in minute inflammatory signs that did not cause clinical symptoms. 25 This raised the possibility that the presence of immune cells deficient for TGF-␤1 is not sufficient to cause the inflammatory phenotype. Alternatively, TGF-␤1-deficient donor cells may be responsive to endocrine or paracrine sources of TGF-␤1 produced by recipient tissues.Further evidence strongly suggests a role of TGF-␤ in the regulation of inflammation using dominant-negative transgenic For personal use only. on May 12, 2018. by guest www.bloodjournal.org From mouse models...

Summary Autoimmune T cell responses directed against insulin‐producing β cells are central to the pathogenesis of type 1 diabetes (T1D). Detection of such responses is therefore critical to provide novel biomarkers for T1D ‘immune staging’ and to understand the mechanisms underlying the disease. While different T cell assays are being developed for these purposes, it is important to optimize and standardize methods for processing human blood samples for these assays. To this end, we review data relevant to critical parameters in peripheral blood mononuclear cell (PBMC) isolation, (cryo)preservation, distribution and usage for detecting antigen‐specific T cell responses. Based on these data, we propose recommendations on processing blood samples for T cell assays and identify gaps in knowledge that need to be addressed. These recommendations may be relevant not only for the analysis of T cell responses in autoimmune disease, but also in cancer and infectious disease, particularly in the context of clinical trials.

OBJECTIVE—Latent autoimmune diabetes in adults (LADA) is often considered a slowly progressing subtype of type 1 diabetes, although the clinical picture more resembles type 2 diabetes. One way to improve classification is to study whether LADA shares genetic features with type 1 and/or type 2 diabetes. RESEARCH DESIGN AND METHODS—To accomplish this, we studied whether LADA shares variation in the HLA locus or INS VNTR and PTPN22 genes with type 1 diabetes or the TCF7L2 gene with type 2 diabetes in 361 LADA, 718 type 1 diabetic, and 1,676 type 2 diabetic patients, as well as 1,704 healthy control subjects from Sweden and Finland. RESULTS—LADA subjects showed, compared with type 2 diabetic patients, increased frequency of risk for the HLA-DQB1 *0201/*0302 genotype (27 vs. 6.9%; P < 1 × 10−6), with similar frequency as with type 1 diabetes (36%). In addition, LADA subjects showed higher frequencies of protective HLA-DQB1 *0602(3)/X than type 1 diabetic patients (8.1 vs. 3.2%, P = 0.003). The AA genotype of rs689, referring to the class I allele in the INS VNTR, as well as the CT/TT genotypes of rs2476601 in the PTPN22 gene, were increased both in type 1 diabetic (P = 3 × 10−14 and P = 1 × 10−10, respectively) and LADA (P = 0.001 and P = 0.002) subjects compared with control subjects. Notably, the frequency of the type 2 diabetes–associated CT/TT genotypes of rs7903146 in the TCF7L2 were increased in LADA subjects (52.8%; P = 0.03), to the same extent as in type 2 diabetic subjects (54.1%, P = 3 × 10−7), compared with control subjects (44.8%) and type 1 diabetic subjects (43.3%). CONCLUSIONS—LADA shares genetic features with both type 1 (HLA, INS VNTR, and PTPN22) and type 2 (TCF7L2) diabetes, which justifies considering LADA as an admixture of the two major types of diabetes.