Center for Beta Cell Therapy in Diabetes

Ongoing beta cell death in type 1 diabetes (T1D) can be detected using biomarkers selectively discharged by dying beta cells into plasma. MicroRNA-375 (miR-375) ranks among top biomarkers based on studies in animal models and human islet transplantation. Our objective was to identify additional microRNAs that are co-released with miR-375 proportionate to the amount of beta cell destruction. RT-PCR profiling of 733 microRNAs in a discovery cohort of T1D patients 1 hour before/after islet transplantation indicated increased plasma levels of 22 microRNAs. Sub-selection for beta cell selectivity resulted in 15 microRNAs that were subjected to double-blinded multicenter analysis. This led to identification of 8 microRNAs that were consistently increased during early graft destruction: besides miR-375, these included miR-132/204/410/200a/429/125b, microRNAs with known function and enrichment in beta cells. Their potential clinical translation was investigated in a third independent cohort of 46 transplant patients, by correlating post-transplant microRNA levels to C-peptide levels 2 months later. Only miR-375 and miR-132 had prognostic potential for graft outcome and none of the newly identified microRNAs outperformed miR-375 in multiple regression. In conclusion, this study reveals multiple beta cell-enriched microRNAs that are co-released with miR-375 and can be used as complementary biomarkers of beta cell death.

Some pesticides increase the risk of type 2 diabetes, but whether fetal exposure carries transgenerational risk remains unknown. We evaluated the metabolic effects of gestational exposure to chlorpyrifos and imidacloprid in female Wistar rats and their offspring. We studied female nulliparous Wistar rats, including six exposed to imidacloprid (IMI) and six to chlorpyrifos (CPF) once daily throughout gestation at 1/10 lethal dose 50, while six (control group) received distilled water. These were explored 1 month after the birth of the offspring, while their offspring were explored at weaning (4weeks) and adult age (12weeks). Blood glucose, insulin and lipid profile were determined at each stage, while glucose transporter 4 (GLUT4) and nuclear factor kappa beta (NFkβ) protein expression was measured in skeletal muscle at the end of follow up. Exposure to pesticides was associated with significantly higher fasting glucose (+25.4 to 30.9%) and insulin (> 100%) levels, with > 100% increased insulin resistance (HOMA-IR), - 18.3 to - 21.1% reduced HDL-cholesterol and + 60.9 to + 102.6% increased LDL-cholesterol in mothers. GLUT4 expression was reduced by 28.9-42.3% while NFkβ expression increased by 32.8-35.4% in mothers. In offspring, similar abnormalities were observed at weaning (+ 18.4 to 67.4% fasting glucose, + 57.1 to 72.2% LDL-cholesterol, + 72.3 to 78.2% fasting insulin), persisting at adult age with decreased expression of GLUT4 (- 52.8 to 54.5%) and increased expression of NFkβ (+ 30.5 to 30.7%). Gestational exposure to imidacloprid and chlorpyrifos induces hyperglycemia, insulin resistance and dyslipidemia in female Wistar rats and their offspring. The effects on offspring persist until adult age, suggesting intergenerational adverse effects.

BackgroundThe hyperglycemic clamp test, the gold standard of beta cell function, predicts impending type 1 diabetes in islet autoantibody-positive individuals, but the latter may benefit from less invasive function tests such as the proinsulin:C-peptide ratio (PI:C). The present study aims to optimize precision of PI:C measurements by automating a dual-label trefoil-type time-resolved fluorescence immunoassay (TT-TRFIA), and to compare its diagnostic performance for predicting type 1 diabetes with that of clamp-derived C-peptide release.MethodsBetween-day imprecision (n = 20) and split-sample analysis (n = 95) were used to compare TT-TRFIA (AutoDelfia, Perkin-Elmer) with separate methods for proinsulin (in-house TRFIA) and C-peptide (Elecsys, Roche). High-risk multiple autoantibody-positive first-degree relatives (n = 49; age 5–39) were tested for fasting PI:C, HOMA2-IR and hyperglycemic clamp and followed for 20–57 months (interquartile range).ResultsTT-TRFIA values for proinsulin, C-peptide and PI:C correlated significantly (r2 = 0.96–0.99; P<0.001) with results obtained with separate methods. TT-TRFIA achieved better between-day %CV for PI:C at three different levels (4.5–7.1 vs 6.7–9.5 for separate methods). In high-risk relatives fasting PI:C was significantly and inversely correlated (rs = -0.596; P<0.001) with first-phase C-peptide release during clamp (also with second phase release, only available for age 12–39 years; n = 31), but only after normalization for HOMA2-IR. In ROC- and Cox regression analysis, HOMA2-IR-corrected PI:C predicted 2-year progression to diabetes equally well as clamp-derived C-peptide release.ConclusionsThe reproducibility of PI:C benefits from the automated simultaneous determination of both hormones. HOMA2-IR-corrected PI:C may serve as a minimally invasive alternative to the more tedious hyperglycemic clamp test.

It is unclear whether ketosis-prone diabetes is a specific type or a subtype of Type 2 diabetes. We aimed to describe the clinical and metabolic features of ketosis-prone diabetes in a sub-Saharan population. We consecutively enrolled and characterized 173 people with non-autoimmune diabetes admitted for hyperglycaemic crisis at the Yaoundé Central Hospital, Cameroon. Blood samples were collected for fasting glucose, HbA1c , lipid profile and C-peptide assays with insulin resistance and secretion estimation by homeostasis model assessment. People were classified as having Type 2 diabetes (n = 124) or ketosis-prone diabetes (n = 49). Ketosis-prone diabetes was sub-classified as new-onset ketotic phase (n = 34) or non-ketotic phase (n = 15). Ketosis-prone diabetes was found in 28.3% of the hyperglycaemic crises. Age at diabetes diagnosis was comparable in Type 2 and ketosis-prone diabetes [48 ± 14 vs 47 ± 11 years; P = 0.13] with a similar sex distribution. Overall BMI was 27.7 ± 13.4 kg/m2 and was ≥ 25 kg/m2 in 55.8% of those taking part, however, 73.5% of those with ketosis-prone diabetes reported weight loss of > 5% at diagnosis. Blood pressure and lipid profile were comparable in both types. Ketosis-prone diabetes in the ketotic phase was characterized by lower insulin secretion and higher serum triglycerides compared with non-ketotic ketosis prone and Type 2 diabetes. Type 2 and ketosis prone diabetes in the non-ketotic phase were comparable in terms of lipid profile, blood pressure, waist-to-hip ratio, BMI and fat mass, insulin secretion and insulin resistance indices. Ketosis-prone diabetes is likely to be a subtype of Type 2 diabetes with the potential to develop acute insulinopenic episodes.

BackgroundIslet cell transplantation holds a potential cure for type 1 diabetes, but many islet recipients do not reach long-lasting insulin independence. In this exploratory study, we investigated whether serum cytokines, chemokines and adipokines are associated with the clinical outcome of islet transplantation.MethodsThirteen islet transplant patients were selected on basis of good graft function (reaching insulin independence) or insufficient engraftment (insulin requiring) from our cohort receiving standardized grafts and immune suppressive therapy. Patients reaching insulin independence were divided in those with continued (>12 months) versus transient (<6 months) insulin independence. A panel of 94 proteins including cytokines and adipokines was measured in sera taken before and at one year after transplantation using a validated multiplex immunoassay platform.ResultsNinety serum proteins were detectable in concentrations varying markedly among patients at either time point. Thirteen markers changed after transplantation, while another seven markers changed in a clinical subpopulation. All other markers remained unaffected after transplantation under generalized immunosuppression. Patterns of cytokines could distinguish good graft function from insufficient function including IFN-α, LIF, SCF and IL-1RII before and after transplantation, by IL-16, CCL3, BDNF and M-CSF only before and by IL-22, IL-33, KIM-1, S100A12 and sCD14 after transplantation. Three other proteins (Leptin, Cathepsin L and S100A12) associated with loss of temporary graft function before or after transplantation.ConclusionsDistinct cytokine signatures could be identified in serum that predict or associate with clinical outcome. These serum markers may help guiding patient selection and choice of immunotherapy, or act as novel drug targets in islet transplantation.

This chapter highlights practical aspects related to aspirin therapy in cardiovascular diseases, specifically, the benefits and hazards in different clinical settings. The absolute benefit of aspirin is linearly related to the risk of the patient. The benefit of aspirin can vary substantially in different settings. For example, in primary prevention in low-risk population, it is not unusual that the number of vascular events avoided equals the number of major bleeds induced by aspirin. In the secondary prevention, the benefits usually outweigh the excess of major bleeding complications. In this setting, the assessment of both bleeding risk and cardiovascular benefits of low-dose aspirin for any individual patient may be difficult in clinical practice. On the other hand, the relatively rare occurrence of major bleeding (gastrointestinal or cerebrovascular) complications should not be underestimated, mainly due to its high morbi-mortality. For all these reasons, in this chapter new developments in the field directed toward individualized risk assessment strategies are discussed.

We evaluated the performance of the Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Cockcroft-Gault (CG) equations against creatinine clearance (CrCl) to estimate glomerular filtration rate (GFR) in 51 patients with Type 2 diabetes. The CrCl value was obtained from the average of two consecutive 24-h urine samples. Results were adjusted for body surface area using the Dubois formula. Serum creatinine was measured using the kinetic Jaffe method and was calibrated to standardized levels. Bland-Altman analysis and kappa statistic were used to examine agreement between measured and estimated GFR. Estimates of GFR from the CrCl, MDRD, CKD-EPI and CG equations were similar (overall P = 0.298), and MDRD (r = 0.58; 95% CI: 0.36-0.74), CKD-EPI (r = 0.55; 95% CI: 0.33-0.72) and CG (r = 0.61; 95% CI: 0.39-0.75) showed modest correlation with CrCl (all P < 0.001). Bias was -0.3 for MDRD, 1.7 for CKD-EPI and -5.4 for CG. All three equations showed fair-to-moderate agreement with CrCl (kappa: 0.38-0.51). The c-statistic for all three equations ranged between 0.75 and 0.77 with no significant difference (P = 0.639 for c-statistic comparison). The MDRD equation seems to have a modest advantage over CKD-EPI and CG in estimating GFR and detecting impaired renal function in sub-Saharan African patients with Type 2 diabetes. The overall relatively modest correlation with CrCl, however, suggests the need for context-specific estimators of GFR or context adaptation of existing estimators.

IntroductionFructosamine is a marker of glucose control reflecting the average glycaemic level over the preceding 2–3 weeks. Fructosamine has not gained as much popularity as glycated haemoglobin (HbA1c) for diabetes mellitus (DM) control monitoring, and the related underlying reasons remain unclear. We aim to search for and summarise available evidence on the accuracy of fructosamine measurements to diagnose and monitor DM.Methods and analysisThis systematic review will include randomised control trials, controlled before-and-after studies, time series designs, cohort studies, case–control studies and cross-sectional surveys reporting the diagnosis and/or monitoring of DM (type 1 DM, type 2 DM and gestational DM) with fructosamine compared with other measures of glycaemia (fasting glucose, oral glucose tolerance test, random glucose, HbA1c), without any language restriction. We will perform electronic searches in PubMed, Scopus and other databases, supplemented with manual searches. Articles published from 1 January 1980 to 30 June 2015 will be eligible for inclusion in this review. Two authors will independently screen, select studies, extract data and assess the risk of bias with discrepancies resolved by consensus. We will assess clinical heterogeneity by examining the types of interventions and outcomes in each study, and pool studies judged to be clinically homogeneous. We will also assess statistical heterogeneity using the χ2 test of homogeneity and quantify it using the I2 statistic. Absolute accuracy measures (sensitivity, specificity) will be pooled in a bivariate random-effects model, allowing for intersetting variability. Negative and positive predictive values will be computed for fructosamine, compared with another measure of glycaemia from the pooled estimates of sensitivity and specificity, using Bayes’ theorem.Ethics and disseminationThis systematic review will use data from published studies and does not require ethics approval. Findings will be published in a peer-reviewed journal and presented at scientific conferences.Trial registration numberPROSPERO (ID=CRD42015015930).

We investigated whether HLA-A*24 typing complements screening for HLA-DQ and for antibodies (Abs) against insulin, GAD, IA-2 (IA-2A), and zinc transporter-8 (ZnT8A) for prediction of rapid progression to type 1 diabetes (T1D). Persistently Ab+ siblings/offspring (n = 288; aged 0–39 years) of T1D patients were genotyped for HLA-DQA1-DQB1 and HLA-A*24 and monitored for development of diabetes within 5 years of first Ab+. HLA-A*24 (P = 0.009), HLA-DQ2/DQ8 (P = 0.001), and positivity for IA-2A ± ZnT8A (P < 0.001) were associated with development of T1D in multivariate analysis. The 5-year risk increased with the number of the above three markers present (n = 0: 6%; n = 1: 18%; n = 2: 46%; n = 3: 100%). Positivity for one or more markers identified a subgroup of 171 (59%) containing 88% of rapid progressors. The combined presence of HLA-A*24 and IA-2A+ ± ZnT8A+ defined a subgroup of 18 (6%) with an 82% diabetes risk. Among IA-2A+ ± ZnT8A+ relatives, identification of HLA-A*24 carriers in addition to HLA-DQ2/DQ8 carriers increased screening sensitivity for relatives at high Ab- and HLA-inferred risk (64% progression; P = 0.002). In conclusion, HLA-A*24 independently predicts rapid progression to T1D in Ab+ relatives and complements IA-2A, ZnT8A, and HLA-DQ2/DQ8 for identifying participants in immunointervention trials.