The PTPN22 C1858T gene variant is associated with proinsulin in new-onset type 1 diabetes

<p>Abstract</p> <p>Background</p> <p>The protein tyrosine phosphatase nonreceptor type 2 (<it>PTPN22</it>) has been established as a type 1 diabetes susceptibility gene. A recent study found the C1858T variant of this gene to be associated with lower residual fasting C-peptide levels and poorer glycemic control in patients with type 1 diabetes. We investigated the association of the C1858T variant with residual beta-cell function (as assessed by stimulated C-peptide, proinsulin and insulin dose-adjusted HbA_1c), glycemic control, daily insulin requirements, diabetic ketoacidosis (DKA) and diabetes-related autoantibodies (IA-2A, GADA, ICA, ZnT8Ab) in children during the first year after diagnosis of type 1 diabetes.</p> <p>Methods</p> <p>The C1858T variant was genotyped in an international cohort of children (n = 257 patients) with newly diagnosed type 1 diabetes during 12 months after onset. We investigated the association of this variant with liquid-meal stimulated beta-cell function (proinsulin and C-peptide) and antibody status 1, 6 and 12 months after onset. In addition HbA_1cand daily insulin requirements were determined 1, 3, 6, 9 and 12 months after diagnosis. DKA was defined at disease onset.</p> <p>Results</p> <p>A repeated measurement model of all time points showed the stimulated proinsulin level is significantly higher (22%, p = 0.03) for the T allele carriers the first year after onset. We also found a significant positive association between proinsulin and IA levels (est.: 1.12, p = 0.002), which did not influence the association between <it>PTPN22 </it>and proinsulin (est.: 1.28, p = 0.03).</p> <p>Conclusions</p> <p>The T allele of the C1858T variant is positively associated with proinsulin levels during the first 12 months in newly diagnosed type 1 diabetes children.</p

Polyp measurement based on CT colonography and colonoscopy: variability and systematic differences

To assess the variability and systematic differences in polyp measurements on optical colonoscopy and CT colonography. Gastroenterologists measured 51 polyps by visual estimation, forceps comparison and linear probe. CT colonography observers randomly assessed polyp size two-dimensionally (abdominal and intermediate window) and three-dimensionally (manually and semi-automatically). Linear mixed models were used to assess the variability and systematic differences between CT colonography and optical colonoscopy techniques. The variability of forceps and linear probe measurements was comparable and both showed less variability than measurement by visual assessment. Measurements by linear probe were 0.7 mm smaller than measurements by visual assessment or by forceps. The variability of all CT colonography techniques was lower than for measurements by forceps or visual assessment and sometimes lower (only 2D intermediate window and manual 3D) compared with measurements by linear probe. All CT colonography measurements judged polyps to be larger than optical colonoscopy, with differences ranging from 0.7 to 2.3 mm. A linear probe does not reduce the measurement variability of endoscopists compared with the forceps. Measurement differences between observers on CT colonography were usually smaller than at optical colonoscopy. Polyps appeared larger when using various CT colonography techniques than when measured during optical colonoscop

Primary uncleansed 2D versus primary electronically cleansed 3D in limited bowel preparation CT-colonography. Is there a difference for novices and experienced readers?

The purpose of this study was to compare a primary uncleansed 2D and a primary electronically cleansed 3D reading strategy in CTC in limited prepped patients. Seventy-two patients received a low-fibre diet with oral iodine before CT-colonography. Six novices and two experienced observers reviewed both cleansed and uncleansed examinations in randomized order. Mean per-polyp sensitivity was compared between the methods by using generalized estimating equations. Mean per-patient sensitivity, and specificity were compared using the McNemar test. Results were stratified for experience (experienced observers versus novice observers). Mean per-polyp sensitivity for polyps 6 mm or larger was significantly higher for novices using cleansed 3D (65%; 95%CI 57–73%) compared with uncleansed 2D (51%; 95%CI 44–59%). For experienced observers there was no significant difference. Mean per-patient sensitivity for polyps 6 mm or larger was significantly higher for novices as well: respectively 75% (95%CI 70–80%) versus 64% (95%CI 59–70%). For experienced observers there was no statistically significant difference. Specificity for both novices and experienced observers was not significantly different. For novices primary electronically cleansed 3D is better for polyp detection than primary uncleansed 2D

Metabolic Regulation in Progression to Autoimmune Diabetes

Recent evidence from serum metabolomics indicates that specific metabolic disturbances precede β-cell autoimmunity in humans and can be used to identify those children who subsequently progress to type 1 diabetes. The mechanisms behind these disturbances are unknown. Here we show the specificity of the pre-autoimmune metabolic changes, as indicated by their conservation in a murine model of type 1 diabetes. We performed a study in non-obese prediabetic (NOD) mice which recapitulated the design of the human study and derived the metabolic states from longitudinal lipidomics data. We show that female NOD mice who later progress to autoimmune diabetes exhibit the same lipidomic pattern as prediabetic children. These metabolic changes are accompanied by enhanced glucose-stimulated insulin secretion, normoglycemia, upregulation of insulinotropic amino acids in islets, elevated plasma leptin and adiponectin, and diminished gut microbial diversity of the Clostridium leptum group. Together, the findings indicate that autoimmune diabetes is preceded by a state of increased metabolic demands on the islets resulting in elevated insulin secretion and suggest alternative metabolic related pathways as therapeutic targets to prevent diabetes

Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond

Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health—Climate Risk framework