Pediatric DiabetesVolume 19, Issue 3 p. 586-586 LETTER TO THE EDITOR It is time to restore Rules for Authorship of scientific publications Johnny Ludvigsson MD, PhD, Johnny Ludvigsson MD, PhD Senior Professor of Pediatrics Johnny.Ludvigsson@liu.se orcid.org/0000-0003-1695-5234 Linköping University, Linköping, SwedenSearch for more papers by this authorPierre Lefebvre MD, PhD, FRCP, MAE, Pierre Lefebvre MD, PhD, FRCP, MAE Emeritus (active) Professor of Medicine University of Liège, Liège, BelgiumSearch for more papers by this authorJørn Nerup, Jørn Nerup Professor Emeritus Steno Diabetes Center, Gentofte/University of Copenhagen, Copenhagen, DenmarkSearch for more papers by this author Johnny Ludvigsson MD, PhD, Johnny Ludvigsson MD, PhD Senior Professor of Pediatrics Johnny.Ludvigsson@liu.se orcid.org/0000-0003-1695-5234 Linköping University, Linköping, SwedenSearch for more papers by this authorPierre Lefebvre MD, PhD, FRCP, MAE, Pierre Lefebvre MD, PhD, FRCP, MAE Emeritus (active) Professor of Medicine University of Liège, Liège, BelgiumSearch for more papers by this authorJørn Nerup, Jørn Nerup Professor Emeritus Steno Diabetes Center, Gentofte/University of Copenhagen, Copenhagen, DenmarkSearch for more papers by this author First published: 09 October 2017 https://doi.org/10.1111/pedi.12572Citations: 3Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article.Citing Literature Volume19, Issue3May 2018Pages 586-586 RelatedInformation

Type 1 diabetes is considered an autoimmune disease characterised by specific T cell-mediated destruction of the insulin-producing beta cells. Yet, except for insulin, no beta cell-specific antigens have been discovered. This may imply that the autoantigens in type 1 diabetes exist in modified forms capable of specifically triggering beta cell destruction. In other immune-mediated diseases, autoantigens targeted by the immune system have undergone post-translational modification (PTM), thereby creating tissue-specific neo-epitopes. In a similar manner, PTM of beta cell proteins might create beta cell-specific neo-epitopes. We suggest that the current paradigm of type 1 diabetes as a classical autoimmune disease should be reconsidered since the immune response may not be directed against native beta cell proteins. A modified model for the pathogenetic events taking place in islets leading to the T cell attack against beta cells is presented. In this model, PTM plays a prominent role in triggering beta cell destruction. We discuss literature of relevance and perform genetic and human islet gene expression analyses. Both direct and circumstantial support for the involvement of PTM in type 1 diabetes exists in the published literature. Furthermore, we report that cytokines change the expression levels of several genes encoding proteins involved in PTM processes in human islets, and that there are type 1 diabetes-associated polymorphisms in a number of these. In conclusion, data from the literature and presented experimental data support the notion that PTM of beta cell proteins may be involved in triggering beta cell destruction in type 1 diabetes. If the beta cell antigens recognised by the immune system foremost come from modified proteins rather than native ones, the concept of type 1 diabetes as a classical autoimmune disease is open for debate.

The common genetic loci that independently influence the risk of type 1 diabetes have largely been determined. Their interactions with age-at-diagnosis of type 1 diabetes, sex, or the major susceptibility locus, HLA class II, remain mostly unexplored. A large collection of more than 14,866 type 1 diabetes samples (6,750 British diabetic individuals and 8,116 affected family samples of European descent) were genotyped at 38 confirmed type 1 diabetes-associated non-HLA regions and used to test for interaction of association with age-at-diagnosis, sex, and HLA class II genotypes using regression models. The alleles that confer susceptibility to type 1 diabetes at interleukin-2 (IL-2), IL2/4q27 (rs2069763) and renalase, FAD-dependent amine oxidase (RNLS)/10q23.31 (rs10509540), were associated with a lower age-at-diagnosis (P = 4.6 × 10−6 and 2.5 × 10−5, respectively). For both loci, individuals carrying the susceptible homozygous genotype were, on average, 7.2 months younger at diagnosis than those carrying the protective homozygous genotypes. In addition to protein tyrosine phosphatase nonreceptor type 22 (PTPN22), evidence of statistical interaction between HLA class II genotypes and rs3087243 at cytotoxic T-lymphocyte antigen 4 (CTLA4)/2q33.2 was obtained (P = 7.90 × 10−5). No evidence of differential risk by sex was obtained at any loci (P ≥ 0.01). Statistical interaction effects can be detected in type 1 diabetes although they provide a relatively small contribution to our understanding of the familial clustering of the disease.

Over 50 regions of the genome have been associated with type 1 diabetes risk, mainly using large case/control collections. In a recent genome-wide association (GWA) study, 18 novel susceptibility loci were identified and replicated, including replication evidence from 2,319 families. Here, we, the Type 1 Diabetes Genetics Consortium (T1DGC), aimed to exclude the possibility that any of the 18 loci were false-positives due to population stratification by significantly increasing the statistical power of our family study.

Objective A large, population-based case–control cohort was used to test the hypothesis that glutamic acid decarboxylase-65 (GAD65) and islet antigen-2 autoantibodies (IA-2A) at birth predict type 1 diabetes. Design and methods The design was an individually matched case–control study of all Danish type 1 diabetes patients born between 1981 and 2002 and diagnosed before May 1 2004 (median age at diagnosis was 8.8 years). Dried blood spot samples collected 5 days after birth in the 1981–2002 birth cohorts and stored at −25 °C were identified from 2023 patients and from two matched controls ( n =4042). Birth data and information on parental age and diabetes were obtained from Danish registers. GAD65A and IA-2A were determined in a radiobinding assay. HLA-DQB1 alleles were analyzed by PCR using time-resolved fluorescence. Results GAD65A and IA-2A were found in 70/2023 (3.5%) patients compared to 21/4042 (0.5%) controls resulting in a hazard ratio (HR) of 7.49 ( P <0.0001). The HR decreased to 4.55 but remained significant ( P <0.0003) after controlling for parental diabetes and HLA-DQB1 alleles. Conditional logistic regression analysis showed a HR of 2.55 ( P <0.0001) for every tenfold increase in the levels of GAD65A and IA-2A. This HR decreased to 1.93 but remained significant ( P <0.001) after controlling for parental diabetes and HLA-DQB1 alleles. Conclusion These data suggest that GAD65A and IA-2A positivity at birth are associated with an increased risk of developing type 1 diabetes in Danish children diagnosed between 1981 and 2004.

Increased glucose excursions and postprandial hyperglycaemia have been suggested as unique risk factors for cardiovascular disease (CVD) and mortality in patients with diabetes mellitus. Much of the evidence is based on a single 2 h glucose value after oral glucose tolerance testing in epidemiological studies. We examined the association between various indices of glycaemia measured during everyday activities and metabolic CVD risk factors in the A1C-Derived Average Glucose (ADAG) study. Participants (268 with type 1 diabetes, 159 with type 2 diabetes) completed 16 weeks of intensive continuous glucose monitoring (CGM) and self-monitoring of blood glucose (SMBG). From these data, common indices of postprandial glycaemia, overall hyperglycaemia, glucose variability and HbA1c were derived. The associations between glycaemic indices and known CVD risk factors (lipids, high-sensitivity C-reactive protein and blood pressure) were explored in linear regression models. For both diabetes types, the overall strongest associations with CVD risk factors were seen for the measures of average glycaemia (mean blood glucose and HbA1c). Associations between self-monitored postprandial and fasting glucose and CVD risk factors were weaker, but significant. Measurements of blood glucose variability showed non-significant associations. Overall, calculations based on CGM were not more informative than those based on frequent SMBG. Mean glycaemia and HbA1c show consistent and stronger associations with CVD risk factors than fasting glucose or postprandial glucose levels or measures of glucose variability in patients with diabetes.

OBJECTIVE Interactions between genetic and environmental factors lead to immune dysregulation causing type 1 diabetes and other autoimmune disorders. Recently, many common genetic variants have been associated with type 1 diabetes risk, but each has modest individual effects. Familial clustering of type 1 diabetes has not been explained fully and could arise from many factors, including undetected genetic variation and gene interactions. RESEARCH DESIGN AND METHODS To address this issue, the Type 1 Diabetes Genetics Consortium recruited 3,892 families, including 4,422 affected sib-pairs. After genotyping 6,090 markers, linkage analyses of these families were performed, using a novel method and taking into account factors such as genotype at known susceptibility loci. RESULTS Evidence for linkage was robust at the HLA and INS loci, with logarithm of odds (LOD) scores of 398.6 and 5.5, respectively. There was suggestive support for five other loci. Stratification by other risk factors (including HLA and age at diagnosis) identified one convincing region on chromosome 6q14 showing linkage in male subjects (corrected LOD = 4.49; replication P = 0.0002), a locus on chromosome 19q in HLA identical siblings (replication P = 0.006), and four other suggestive loci. CONCLUSIONS This is the largest linkage study reported for any disease. Our data indicate there are no major type 1 diabetes subtypes definable by linkage analyses; susceptibility is caused by actions of HLA and an apparently random selection from a large number of modest-effect loci; and apart from HLA and INS, there is no important susceptibility factor discoverable by linkage methods.

OBJECTIVE Various methods are used to quantify postprandial glycemia or glucose variability, but few have been compared and none are standardized. Our objective was to examine the relationship among common indexes of postprandial glycemia, overall hyperglycemia, glucose variability, and A1C using detailed glucose measures obtained during everyday life and to study which blood glucose values of the day provide the strongest prediction of A1C. RESEARCH DESIGN AND METHODS In the A1C-Derived Average Glucose (ADAG) study, glucose levels were monitored in 507 participants (268 type 1 diabetic, 159 type 2 diabetic, and 80 nondiabetic subjects) with continuous glucose monitoring (CGM) and frequent self-monitoring of blood glucose (SMBG) during 16 weeks. We calculated several indexes of glycemia and analyzed their intercorrelations. The association between glucose measurements at different times of the day (pre- and postprandial) and A1C was examined using multiple linear regression. RESULTS Indexes of glucose variability showed strong intercorrelation. Among postprandial indexes, the area under the glucose curve calculated from CGM 2 h after a meal correlated well with the 90-min SMBG postprandial measurements. Fasting blood glucose (FBG) levels were only moderately correlated with indexes of hyperglycemia and average or postprandial glucose levels. Indexes derived with SMBG strongly correlated with those from CGM. Some SMBG time points had a stronger association with A1C than others. Overall, preprandial glucose values had a stronger association with A1C than postprandial values for both diabetes types, particularly for type 2 diabetes. CONCLUSIONS Indexes of glucose variability and average and postprandial glycemia intercorrelate strongly within each category. Variability indexes are weakly correlated with the other categories, indicating that these measures convey different information. FBG is not a clear indicator of general glycemia. Preprandial glucose values have a larger impact on A1C levels than postprandial values.

Aims/hypothesis Real-life glycaemic profiles of healthy individuals are poorly studied. Our aim was to analyse to what extent individuals without diabetes exceed OGTT thresholds for impaired glucose tolerance (IGT) and diabetes. Methods In the A1C-Derived Average Glucose (ADAG) study, 80 participants without diabetes completed an intensive glucose monitoring period of 12 weeks. From these data, we calculated the average 24 h glucose exposure as time spent above different plasma glucose thresholds. We also derived indices of postprandial glucose levels, glucose variability and HbA 1c . Results We found that 93% of participants reached glucose concentrations above the IGT threshold of 7.8 mmol/l and spent a median of 26 min/day above this level during continuous glucose monitoring. Eight individuals (10%) spent more than 2 h in the IGT range. They had higher HbA 1c , fasting plasma glucose (FPG), age and BMI than those who did not. Seven participants (9%) reached glucose concentrations above 11.1 mmol/l during monitoring. Conclusions/interpretation Even though the non-diabetic individuals monitored in the ADAG study were selected on the basis of a very low level of baseline FPG, 10% of these spent a considerable amount of time at glucose levels considered to be ‘prediabetic’ or indicating IGT. This highlights the fact that exposure to moderately elevated glucose levels remains under-appreciated when individuals are classified on the basis of isolated glucose measurements.

text has not been submitted. Review on this subject by the lecturer: J Intern Med. 2009 May;265(5):51429. Clinical manifestations and management of patients with autoimmune polyendocrine syndrome type I. Husebye ES, Perheentupa J, Rautemaa R, Kämpe O. Section of Endocrinology, Institute of Medicine, University of Bergen, Bergen, Norway. eyhu@helse-bergen.no. Abstract. Autoimmune polyendocrine syndrome type I (APS-I) is a monogenic model disease of autoimmunity. Its hallmarks are chronic mucocutaneous candidosis, hypoparathyroidism and adrenal insufficiency, but many other Autoimmune polyendocrine syndrome type I (APS-I) is a monogenic model disease of autoimmunity. Its hallmarks are chronic mucocutaneous candidosis, hypoparathyroidism and adrenal insufficiency, but many other autoimmune disease components occur less frequently. The first components usually appear in childhood, but may be delayed to adolescence or early adult life. There is enormous variation in presentation and phenotype, which makes the diagnosis difficult. Antibodies against interferon-omega and -alpha have recently been shown to be sensitive and relatively specific markers for APS-I, and mutational analysis of the autoimmune regulator gene gives the diagnosis in >95% of cases. The treatment and follow-up of patients is demanding and requires the collaboration of specialists of several fields. However, the literature is especially sparse regarding information on treatment and follow-up; hence, we present here a comprehensive overview on clinical characteristics, treatment and follow-up based on personal experience and published studies. PL2 Novel Avenues in Energy Metabolism PL2-3 How the fetal hypothalamus senses maternal glucose metabolism Jens C. Brüning University of Cologne, and Center of Molecular Medicine Cologne, Department of Mouse Genetics and Metabolism, Institute for Genetics, Cologne, Germany Abstract text has not been submitted.text has not been submitted. Review on this subject by the lecturer. Cell Mol Life Sci. 2010 Oct;67(19):3255-73. Epub 2010 Jun 12. Sensing the fuels: glucose and lipid signaling in the CNS controlling energy homeostasis. Jordan SD, Könner AC, Brüning JC. Department of Mouse Genetics and Metabolism, Institute for Genetics and Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (CECAD), University of Cologne, Zülpicher Strasse 47, 50674 Cologne, Germany. Abstract. The central nervous system (CNS) is capable of gathering The central nervous system (CNS) is capable of gathering information on the body's nutritional state and it implements appropriate behavioral and metabolic responses to changes in fuel availability. This feedback signaling of peripheral tissues ensures the maintenance of energy homeostasis. The hypothalamus is a primary site of convergence and integration for these nutrient-related feedback signals, which include central and peripheral neuronal inputs as well as hormonal signals. Increasing evidence indicates that glucose and lipids are detected by specialized fuel-sensing neurons that are integrated in these hypothalamic neuronal circuits. The purpose of this review is to outline the current understanding of fuel-sensing mechanisms in the hypothalamus, to integrate the recent findings in this field, and to address the potential role of dysregulation in these pathways in the development of obesity and type 2 diabetes mellitus. Concluding Remarks. The global prevalence of obesity and diabetes mellitus is increasing at an alarming rate and dysregulation of the central control of energy homeostasis has been posited as a causative mechanism of these metabolic diseases. Besides the capability of selective brain regions, especially the hypothalamus, to integrate a variety of neuronal and hormonal signals, increasing evidence indicates that fuel sensing also plays a pivotal role in the central regulation of food intake, energy expenditure, and glucose homeostasis. Recent progress has confirmed the presence of distinct hypothalamic neuron populations that respond to changes in circulating nutrient concentrations by either activating or inhibiting their firing activity. At the molecular level, some proteins required for neuronal fuel sensing have already been identified. Among them, KATP channels and the well-known fuel sensor AMPK represent critical points of interaction between hypothalamic glucose and lipid sensing. A wide range of data further implicates the modulation of neuronal fuel sensing by a variety of hormones such as insulin, leptin, and ghrelin, leading to an increased degree of complexity in the response of these neurons to changes in wholebody energy level. Beyond the scope of this review is another relative new concept in central nutrient sensing involving the role of amino acids in the regulation of energy homeostasis. Studies have demonstrated that increasing or decreasing the dietary intake of leucine, a branched-chain amino acid, as well as ICV administration of this amino acid affects glucose metabolism and food intake. The latter was attributed to changes in hypothalamic Agouti-related protein (AgRP) expression and mechanistically linked to mammalian target of rapamycine (mTOR). A better understanding of the complex interaction of nutrients, hormones, and neuronal circuitries in the modulation of central behavioral and metabolic output signals might point to novel interventions to prevent or treat obesity and type 2 diabetes mellitus. PL2-4 A paradigm of integrative physiology, the crosstalk between bone and energy metabolisms Gerard Karsenty Columbia University Medical Center, Genetics & Development, New York, United States Our laboratory has been testing the hypothesis that bone mass and energy metabolism are co-regulated. This led us first to show that leptin that is made in adipocytes inhibits both bone mass accrual and appetite by inhibiting serotonin synthesis and release by brainstem neurons. Having identified this regulatory loop and many of its molecular components we then asked whether bone was an endocrine organ regulating energy metabolism. This line of research allowed us to show that the osteoblast-specific secreted molecule osteocalcin favors, when undercarboxylated, insulin secretion, insulin sensitivity and energy expenditure. We further showed that osteoblasts express another gene, Esp, that encodes a tyrosine phosphatase and acts as an inhibitor of osteocalcin decarboxylation. How an intracellular tyrosine phosphatase could regulate the carboxylation statues of a secreted molecule like osteocalcin is unknown. Likewise, we do not know what is the human equivalent, if it exists, of Esp that is pseudogene in humans. We have embarked in a systematic study, using biochemical, molecular biology and genetics as tools to answer these two questions. Publications on this subject by the lecturer. Cell Biol. 2010 Oct 4;191(1):7-13. J. The two faces of serotonin in bone biology. Ducy P, Karsenty G. Department of Pathology and Cell Biology and 2 Department of Genetics and Development, Columbia University Medical Center, New York, NY 10032. Abstract. The serotonin molecule has some remarkable properties. It is synthesized by two different genes at two different sites, and, surprisingly, plays The serotonin molecule has some remarkable properties. It is synthesized by two different genes at two different sites, and, surprisingly, plays antagonistic functions on bone mass accrual at these two sites. When produced peripherally, serotonin acts as a hormone to inhibit bone formation. In contrast, when produced in the brain, serotonin acts as a neurotransmitter to exert a positive and dominant effect on bone mass accrual by enhancing bone formation and limiting bone resorption. The effect of serotonin on bone biology could be harnessed pharmacologically to treat diseases such as osteoporosis. Cell. 2010 Jul 23;142(2):296-308. Insulin signaling in osteoblasts integrates bone remodeling and energy metabolism. Ferron M, Wei J, Yoshizawa T, Del Fattore A, DePinho RA, Teti A, Ducy P, Karsenty G. Department of Genetics and Development, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA. Comment in: Cell. 2010 Jul 23;142(2):198-200. Abstract. The broad expression of the insulin receptor suggests that the spectrum of insulin function has not been fully described. A cell type expressing this receptor is the osteoblast, a bone-specific cell favoring glucose metabolism through a hormone, osteocalcin, that becomes active once uncarboxylated. We show here that insulin signaling in osteoblasts is necessary for whole-body glucose homeostasis because it increases osteocalcin activity. To achieve this function insulin signaling in osteoblasts takes advantage of the regulation of osteoclastic bone resorption exerted by osteoblasts. Indeed, since bone resorption occurs at a pH acidic enough to decarboxylate proteins, osteoclasts determine the carboxylation status and function of osteocalcin. Accordingly, increasing or decreasing insulin signaling in osteoblasts promotes or hampers glucose metabolism in a bone resorption-dependent manner in mice and humans. Hence, in a feed-forward loop, insulin signals in osteoblasts activate a hormone, osteocalcin, that promotes glucose metabolism. The broad expression of the insulin receptor suggests that the spectrum of insulin function has not been fully described. A cell type expressing this receptor is the osteoblast, a bone-specific cell favoring glucose metabolism through a hormone, osteocalcin, that becomes active once uncarboxylated. We show here that insulin signaling in osteoblasts is necessary for whole-body glucose homeostasis because it increases osteocalcin activity. To achieve this function insulin signaling in osteoblasts takes advantage of the regulation of osteoclastic bone resorption exerted by osteoblasts. Indeed, since bone resorption occurs at a pH acidic enough to decarboxylat

The discovery of the association between HLA in the major histocompatibility complex (MHC) on chromosome 6p21 with type 1 diabetes, but not with type 2 diabetes, suggested that these disease entities were of different genetic background and pathogenesis. The discovery that some individuals with diabetes had autoantibodies in their blood provided additional evidence that type 1 diabetes had an autoimmune origin. Recently, increasing knowledge of the genome, coupled with rapidly improving genotyping technology and availability of increasingly large numbers of samples, has enabled statistically robust, systematic, genome-wide examinations for discovery of loci contributing to type 1 diabetes susceptibility, including within the MHC itself. Currently, there are over 50 non-HLA regions that significantly affect the risk for type 1 diabetes (http://www.t1dbase.org). Many of these regions contain interesting, but previously unrecognized, candidate genes. A few regions contain genes of unknown function or no known annotated genes, suggesting roles for long-distance gene regulatory effects, noncoding RNAs, or unknown mechanisms. Against a background of ever-improving knowledge of the genome, particularly its transcriptional regulation, and with massive advances in sequencing, specific genes, rather than regions that impinge upon type 1 diabetes risk, will be identified soon. Here we discuss follow-up strategies for genome-wide association (GWA) studies, causality of candidate genes, and genetic association in a bioinformatics approach with the anticipation that this knowledge will permit identification of the earliest events in type 1 diabetes etiology that could be targets for intervention or biomarkers for monitoring the effects and outcomes of potential therapeutic agents. The International Type 1 Diabetes Genetics Consortium (T1DGC) has established significant resources for the study of genetics of type 1 diabetes. These resources are available to the research community and provide a basis for future discovery in the transition from gene mapping to discovery of disease mechanisms. The T1DGC (http://www.t1dgc.org) is an …

Patrick Concannon and colleagues present a type 1 diabetes genome-wide association study and meta-analysis in 7,514 cases and 9,045 reference samples, reporting 22 newly identified loci. Type 1 diabetes (T1D) is a common autoimmune disorder that arises from the action of multiple genetic and environmental risk factors. We report the findings of a genome-wide association study of T1D, combined in a meta-analysis with two previously published studies. The total sample set included 7,514 cases and 9,045 reference samples. Forty-one distinct genomic locations provided evidence for association with T1D in the meta-analysis (P < 10−6). After excluding previously reported associations, we further tested 27 regions in an independent set of 4,267 cases, 4,463 controls and 2,319 affected sib-pair (ASP) families. Of these, 18 regions were replicated (P < 0.01; overall P < 5 × 10−8) and 4 additional regions provided nominal evidence of replication (P < 0.05). The many new candidate genes suggested by these results include IL10, IL19, IL20, GLIS3, CD69 and IL27.

Aims/hypothesis: The suppressor of cytokine signalling 1 (SOCS1) is a natural inhibitor of cytokine and insulin signalling pathways and may also play a role in obesity. In addition, SOCS1 is considered a candidate gene in the pathogenesis of both type 1 diabetes (T1D) and type 2 diabetes (T2D). The objective was to perform mutation analysis of SOCS1 and to test the identified variations for association to T2D‐related quantitative traits, T2D or T1D. Methods: Mutation scanning was performed by direct sequencing in 27 white Danish subjects. Genotyping was carried out by TaqMan allelic discrimination. A total of more than 8100 individuals were genotyped. Results: Eight variations were identified in the 5′ untranslated region (UTR) region. Two of these had allele frequencies below 1% and were not further examined. The six other variants were analysed in groups of T1D families (n = 1461 subjects) and T2D patients (n = 1430), glucose tolerant first‐degree relatives of T2D patients (n = 212) and normal glucose tolerant (NGT) subjects. The rs33977706 polymorphism (−820G > T) was associated with a lower body mass index (BMI) (p = 0.004). In a second study (n = 4625 NGT subjects), significant associations of both the rs33977706 and the rs243330 (−1656G > A) variants to obesity were found (p = 0.047 and p = 0.015) respectively. The rs33977706 affected both binding of a nuclear protein to and the transcriptional activity of the SOCS1 promoter, indicating a relationship between this polymorphism and gene regulation. Conclusions/interpretation: This study demonstrates that functional variations in the SOCS1 promoter may associate with alterations in BMI in the general white population.

The high-risk human leukocyte antigen (HLA)-DRB1, DQA1 and DQB1 alleles cannot explain the entire type 1 diabetes (T1D) association observed within the extended major histocompatibility complex. We have earlier identified an association with D6S2223, located 2.3 Mb telomeric of HLA-A, on the DRB1(*)03-DQA1(*)0501-DQB1(*)0201 haplotype, and this study aimed to fine-map the associated region also on the DRB1(*)0401-DQA1(*)03-DQB1(*)0302 haplotype, characterized by less extensive linkage disequilibrium. To exclude associations secondary to DRB1-DQA1-DQB1 haplotypes, 205 families with at least one parent homozygous for these loci, were genotyped for 137 polymorphisms. We found novel associations on the DRB1(*)0401-DQA1(*)03-DQB1(*)0302 haplotypic background with eight single nucleotide polymorphisms (SNPs) located within or near the PRSS16 gene. In addition, association at the butyrophilin (BTN)-gene cluster, particularly the BTN3A2 gene, was observed by multilocus analyses. We replicated the associations with SNPs in the PRSS16 region and, albeit weaker, to the BTN3A2 region, in an independent material of 725 families obtained from the Type 1 Diabetes Genetics Consortium. It is important to note that these associations were independent of the HLA-DRB1-DQA1-DQB1 genes, as well as of associations observed at HLA-A, -B and -C. Taken together, our results identify PRSS16 and BTN3A2, two genes thought to play important roles in regulating the immune response, as potentially novel susceptibility genes for T1D.

Glycated haemoglobin (HbA 1c ) is widely used to determine levels of chronic glycaemia, to judge the adequacy of diabetes treatment and to adjust therapy. HbA 1c results are expressed as the percentage of HbA that is glycated. Day-to-day management is guided by self-monitoring of capillary glucose concentrations in mmol/l. The ADAG study determined the relationship between HbA 1c and average glucose concentration (AG) and concluded that for most patients with diabetes, HbA 1c can - with reasonable precision - be expressed as an estimated AG in the same units as self-monitoring.

The Type I Diabetes Genetics Consortium (T1DGC) is an international, multicenter research program with two primary goals. The first goal is to identify genomic regions and candidate genes whose variants modify an individual's risk of type I diabetes (T1D) and help explain the clustering of the disease in families. The second goal is to make research data available to the research community and to establish resources that can be used by, and that are fully accessible to, the research community. To facilitate the access to these resources, the T1DGC has developed a Consortium Agreement ( http://www.t1dgc.org ) that specifies the rights and responsibilities of investigators who participate in Consortium activities. The T1DGC has assembled a resource of affected sib-pair families, parent–child trios, and case–control collections with banks of DNA, serum, plasma, and EBV-transformed cell lines. In addition, both candidate gene and genome-wide (linkage and association) studies have been performed and displayed in T1DBase ( http://www.t1dbase.org ) for all researchers to use in their own investigations. In this supplement, a subset of the T1DGC collection has been used to investigate earlier published candidate genes for T1D, to confirm the results from a genome-wide association scan for T1D, and to determine associations with candidate genes for other autoimmune diseases or with type II diabetes that may be involved with β-cell function.

A CA-repeat polymorphism within the first intron of the interferon (IFN)-gamma gene was analyzed. This polymorphism was recently demonstrated to be associated with insulin-dependent diabetes mellitus (IDDM) in Japanese subjects. We typed 266 IDDM patients and 195 control subjects of Danish Caucasoid origin. No significant differences in allele or genotype frequencies between patients and control were observed. In addition, we typed 168 IDDM and 110 control subjects of Finnish origin. A significant disease association of the studied IFN-gamma allelic pattern was found (p = 0.029). Analysis of data according to HLA-DQB1 susceptibility status did not reveal heterogeneity of risk at the IFN-gamma locus in either of the populations. Fifty-five Danish and 94 Finnish IDDM multiplex families with at least two affected siblings (660 individuals) were typed to test for transmission disequilibrium (TDT). No evidence for overall transmission disequilibrium using either an allele-wise (p = 0.42; combined data) or a genotype-wise analysis (p = 0.21; combined data) could be detected. Thus, the modest significance level observed in the Finnish case-control study and the failure to replicate it by the TDT provide little support for the hypothesis that the IFN-gamma gene microsatellite is associated with IDDM.