Mutation analysis of suppressor of cytokine signalling 3, a candidate gene in Type 1 diabetes and insulin sensitivity

Aims/hypothesis Beta cell loss in Type 1 and Type 2 diabetes mellitus may result from apoptosis and necrosis induced by inflammatory mediators. The suppressor of cytokine signalling (SOCS)-3 is a natural inhibitor of cytokine signalling and also influences insulin signalling. SOCS3 could therefore be a candidate gene in the development of Type 1 and Type 2 diabetes mellitus.Methods Mutation analysis of the SOCS3 gene was performed in 21 patients with Type 1 diabetes mellitus and in seven healthy subjects. An identified promoter variant was examined in (i) 250 families with Type 1 diabetic family members (1097 individuals); (ii) 212 glucose-tolerant first-degree relatives of Type 2 diabetic patients; and (iii) 370 population-based young, healthy subjects who were unrelated.Results Three mutations were identified in the promoter region, but none in the coding region or the 3UTR. Two of the three mutations had allele frequencies below 1% whereas the C –920A substitution had a minor allele frequency of 8%. In the group of young healthy subjects the insulin sensitivity index was higher among homozygous carriers of the A-allele than among heterozygous and wild-type subjects (p=0.027, uncorrected). The same trend was found in the group of first-degree relatives of Type 2 diabetic patients. No association or linkage was found to Type 1 diabetes mellitus.Conclusions/interpretation Homozygosity for the A-allele of the C –920A promoter polymorphism of the SOCS3 gene may be associated with increased whole-body insulin sensitivity, but deserves further investigation.Abbreviations AIR acute insulin response - AP2 activator protein 2 - GH growth hormone - SI Insulin sensitivity index - Sib-TDT Sib Transmission Disequilibrium Test - SNP single nucleotide polymorphism - SOCS suppressor of cytokine signalling - SSCP single-strand conformational polymorphism     

Rapid changes in chromatographically determined haemoglobin A1c induced by short-term changes in glucose concentration

Summary Chromatographically determined haemoglobin A_1c concentration was measured during short-term (1–24 h) changes in glucose concentration in vitro and in vivo. In vitro at 37 °C the HbA_1c concentration increased with glucose concentration and time both in normal and diabetic erythrocytes. In normal erythrocytes incubated in 20–100 mmol/l glucose, the increases in the HbA_1c concentration were maximal after 4–6 h and then stable for the next 18–20 h. During the first hour, increases in the HbA_1c concentration were linear with time and on average 0.034% HbA_1c × h^–1 × mmol/l glucose^–1. In erythrocytes, after a rapidly produced increase (2h), HbA_1c decreased to preincubation concentrations during a further incubation of the erythrocytes in a glucose-free medium at 37 °C for 4–6 h. The mean rate of linear decrease was 0.017% × h^–1 × mmol/l glucose^–1. After incubation of erythrocytes in 100 mmol/l glucose for 24 h, 1.3% HbA_1c remained stable for 6 h in saline. The rapid increase in HbA_1c concentration, as determined by chromatography, was not due to stable HbA_1c (ketoamine linked glucose) as no increase was found in the HbA_1c concentrations determined by the thiobarbiturate method. In juvenile diabetics controlled by an artificial beta-cell, rapid changes of blood glucose concentration (up to 20 mmol/l) resulted in increases in HbA_1c concentration of as much as 1.9% within 12 h (mean 1.1%). Rapid in vivo increases in HbA_1c concentration were reversible by normalization of the blood glucose concentration. That rapid changes in HbA_1c may occur in daily diabetic life was evidenced by differences in HbA_1c concentration between blood samples from out-patient diabetics incubated in saline for 16 hours at 4 °C and 37 °C (range of differences 0.2–1.4% HbA_1c). The differences correlated to the blood glucose concentration at the time of sampling blood for HbA_1c determination. Thus, incubation of blood at a low glucose concentration prior to determination of the glycosylated haemoglobin concentration may overcome interference from rapidly produced HbA_1c.     

A peptide agonist of the neural cell adhesion molecule (NCAM), C3, protects against developmental defects induced by a teratogen pyrimethamine.

The neural cell adhesion molecule, NCAM, not only plays an important role in neuronal migration, differentiation and formation of connections in the developing nervous system, but also in the condensation of the mesodermal mesenchyme of the limb bud. Therefore, NCAM may be regarded as a target molecule for preventive strategies aimed at minimizing the effects of teratogens affecting the prenatal development of the nervous system and the skeleton. Treatment of fetuses with the teratogen pyrimethamine results in a reduced body weight, microcephaly and malformations of the hind limbs and forelimbs, e.g. micromelia, brachydactyly and adactyly. We here show that a peptide agonist of NCAM, C3, partly prevented the defects induced by this treatment. Although intra-amniotic administration of C3 at gestational day 14 had no effect on the pyrimethamine-induced reduction in body weight, it rescued the deficit in brain weight (microcephaly), partly reversed a decrease in thickness of the cortical plate, and significantly reduced the number of malformed fetuses. In vitro, C3 promoted survival of PC12-E2 cells treated with pyrimethamine. Since C3 is a peptide mimetic of NCAM, our data strongly suggest that stimulating of NCAM results in neuroprotection in vivo and in vitro.     

Synthesis of glycosylated haemoglobin in vivo

Summary The synthesis of glycosylated haemoglobins in vivo was measured during 24 h of controlled hyperglycaemia in seven insulin dependent diabetics. The mean blood glucose concentration was 22 mmol/l, while electrolytes and other metabolites were kept normal by infusion of 4–23 IU of insulin during hyperglycaemia. The study confirmed the velocity and magnitude of unstable HbA_1c formation previously found in vitro. The stable HbA_1c formed in 24 h was on average 0.006% of total haemoglobin/ mmol glucose. This compares well with the rate of HbA_1c synthesis reported in normal subjects using ⁵⁹Fe-kinetic measurements, and is in accordance with the concept of slow changes in stable HbA_1c with time and glucose concentration. To investigate the possibility that the rate of HbA_1c synthesis varies with erythrocyte age, glycosylated haemoglobins were measured in erythrocyte fractions after density separation on Percoll-Albumin gradients. We found both in normal subjects and in insulin treated diabetics that the 5% least dense cells contained 70%–80% of whole blood HbA_1c. Assuming the least dense cells to be the youngest erythrocytes, this observation is inconsistent with a slow linear increase in HbA_1c. Similar results were obtained in six newly diagnosed insulin dependent diabetic patients both before and after the first 30 days of insulin treatment, even though a marked decrease in young cell HbA_1c would be expected with the improved glucose control observed. We therefore conclude that density separation of erythrocytes is an inadequate technique to study age related HbA_1c synthesis.     

Protein expression changes in a cell system of beta-cell maturation reflect an acquired sensitivity to IL-1β

Aim/hypothesis Type 1 diabetes mellitus (T1DM) is caused by specific destruction of the pancreatic beta cells in the islets of Langerhans. Increased sensitivity to cytokines, in particular to interleukin-1 (IL-1) seems to be an acquired trait during beta-cell maturation. In response to cytokines both protective and deleterious mechanisms are induced in beta cells, and when the deleterious prevail, T1DM develops. The aims of this study were to identify perturbation in protein patterns (PiPP) associated with beta-cell maturation, and compare these changes to previous analyses of IL-1 exposed rat islets. For this purpose, proteome analyses were carried out using a cell-line, which matures from a glucagon-producing pre-beta-cell phenotype (NHI-glu) to an insulin-producing beta-cell phenotype (NHI-ins). We have previously shown that this maturation is accompanied by acquired sensitivity to the toxic effects of IL-1.Methods 2D-gel electrophoresis was used to separate the proteins and MALDI-MS and database searches were performed to identify the proteins.Results During beta-cell maturation 135 protein spots out of 2239 detectable changed expression levels. Of these, 74 were down-regulated, 44 up-regulated, 16 were suppressed and 1 was expressed de novo. Using MALDI-MS, positive identification was obtained for 93 out of the 135 protein-spots revealing 97 different proteins. Of these, 22 proteins were in common with changes identified in previous proteome analysis of perturbation in protein pattern in IL-1 exposed rat islets. Several of the proteins were present in more than one spot suggesting post-translational modification.Conclusion/interpretation Several proteins and protein modifications were identified that could be critically involved in beta-cell maturation, insulin-gene expression and the acquired IL-1 sensitivity.Abbreviations T1DM Type 1 diabetes mellitus - PiPP perturbation in protein pattern - NO nitric oxide - iNOS inducible nitric oxide synthase - 2D-GE 2 dimensional gel electrophoresis - IEF isoelectric focusing - NEPHGE non-equilibrium pH-gradient electrophoresis - WF Wistar Furth - BB Bio Breeding - PDX-1 pancreatic duodenum homeobox 1 - ASS argininosuccinate synthetase - HSP heat shock protein - Picot PKC-interacting cousin of thioredoxin - JNK Jun N-terminal kinase - VDAC voltage-dependent anion channel - GST glutathione-S-transferase - Mw molecular weight - pI isoelectric point     

Evidence of Gene-Gene Interaction and Age-at-Diagnosis Effects in Type 1 Diabetes

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.Knowledge of the genetic architecture of type 1 diabetes has increased recently owing to large-scale genome-wide association (GWA) studies (1–3). Estimates of the contributions of the HLA region and numerous non-HLA loci across the genome now account for a sizeable proportion of familial clustering of the disorder (4–6). However, there remains substantial familial clustering that is not explained by the known loci (likely to be in excess of 40%) (4–6). Interactions between risk loci beyond that of a multiplicative model on the odds ratio (OR) scale (or additive on the log odds scale (7)) could account for some of the “missing heritability.” In addition, the existence of differential effects according to age-at-diagnosis and sex remains relatively unexplored.The HLA region on chromosome 6p21 is the major source of familial clustering in type 1 diabetes (4). HLA-DRB1 and HLA-DQB1 are associated with ORs in excess of 10 for susceptible genotypes (or less than 0.1 for protective genotypes) (8). The risk genotype HLA-DRB1*03/HLA-DRB1*04-HLA-DQB1*0302 (referred to as DR3/DR4-DQ302) with greatest effect has been shown to have the highest frequency in the individuals with youngest onset (9). An age-at-diagnosis interaction has also been reported for HLA-DRB1*04 (10) and the HLA class I alleles HLA-A*24 and HLA-B*39 (11,12).In contrast, reports of age-at-diagnosis interaction effects at non-HLA loci are contradictory, with positive reports largely confined to studies involving small sample sets (3,13–15). Similarly, reports of gene–gene interaction of type 1 diabetes–associated regions are also mainly conflicting (16–19), we presume due to inadequate sample sizes, with most positive reports likely to be false because the false-discovery rate would be high in these underpowered studies. The only convincing gene–gene interaction reported, is between a major non-HLA locus, protein tyrosine phosphatase nonreceptor type 22 (PTPN22) and DR3/DR4-DQ302 genotypes (20–23).The incidence of childhood type 1 diabetes is similar in males and females, unlike other autoimmune diseases such as Graves disease, celiac disease, or multiple sclerosis. Despite similar frequencies of childhood type 1 diabetes by sex, there have been reports of genetic risk factors differing between males and females (22,24).Given that most studies of gene–gene interaction, age-at-diagnosis effects, and sex effects on type 1 diabetes risk have not been addressed in sufficiently well-powered studies, the Type 1 Diabetes Genetics Consortium (T1DGC) has collected more than 16,000 type 1 diabetes–affected samples and tested them for interaction effects with sex and age-at-diagnosis at 38 non-HLA type 1 diabetes–associated regions (Supplementary Table 2). Gene–gene interaction was also tested between HLA class II and the 38 non-HLA loci. With this very large sample set, the study had at least 80% power to detect effects as small as an interaction OR = 1.12 for sex and 1.19 for interactions with age-at-diagnosis or HLA. These calculations assume a multiplicative (log additive) effects model, an OR = 1.15 for association with type 1 diabetes for the test locus and a minor allele frequency of 0.2 and α = 0.0004. In contrast, with 5,000 samples, which is twice as large as any other study testing for interaction effects in type 1 diabetes published to date, the study would only be powered at 80% to detect interaction effects larger than an OR = 1.3 with sex (with the same assumptions as above). For age-at-diagnosis interaction, an OR ≥ 1.37 could be detected; for HLA interaction, an OR ≥ 1.38 could be detected (Supplementary Figs. 1–6).     

Histopathologische Veränderungen des Blutes bei Einwirkung hoher Temperatur

Ohne ZusammenfassungMit 17 Abbildungen im Text.Vorgetragen in der wissenschaftlichen Sitzungskonferenz Iwanovo-Wosnessensk Med. Institut am 23. November 1932.