The Systemic Immune Network in Recent Onset Type 1 Diabetes: Central Role of Interleukin-1 Receptor Antagonist (DIATOR Trial)

Background

The hypothesis was tested that the systemic immune milieu in recent-onset type 1 diabetes is associated with residual beta cell function and other metabolic patient characteristics.

Methods and Findings

All patients (n = 89, 40% female) of the Diabetes and Atorvastatin (DIATOR) Trial were analyzed at recruitment, i.e. prior to receiving the study medication. Inclusion criteria were insulin dependent diabetes for 2 weeks to 3 months, age range 18–39 years, and islet cell autoantibodies. Blood samples were analyzed for 14 immune mediators by standard methods. Concentrations of all mediators correlated with at least one other mediator (p<0.05, Spearman correlation) giving rise to a network. Interleukin 1 receptor antagonist (IL1-RA) held a central position and was associated with both pro- and anti-inflammatory mediators. Further central elements were the pro-inflammatory mediators CRP and IL-6, the soluble adhesion molecules sICAM-1 and E-selectin, and MCP-4 which held a central position in the chemokine network. The two Th1-associated mediators IFNγ and IP-10 remained outside the network but correlated with each other. All correlations were positive (r = 0.25–0.72), i.e., high levels of pro-inflammatory mediators were accompanied by increased levels of anti-inflammatory mediators. IL-1RA was the only mediator associated with fasting and liquid mixed meal stimulated C-peptide concentrations (r = 0.31 and 0.24, p = 0.003 and 0.025, after adjustment for age, sex, BMI). There were associations between the immune mediator network and BMI (IL-1RA, CRP, IL-6, MCP-4, MIP-1ß) but few or no associations with HbA1c, insulin dose, lipid parameters, age or sex.

Conclusions

In patients with recent onset type 1 diabetes, systemic acute phase proteins, cytokines, chemokines and soluble adhesion molecules form a network. Among the few central elements IL-1RA has a dominant role. IL-1RA is associated with all other groups of mediators and is the only mediator which correlates (positively) with residual beta cell function.

Trial registration

ClinicalTrials.gov registration number: {"type":"clinical-trial","attrs":{"text":"NCT00974740","term_id":"NCT00974740"}}NCT00974740     

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Metabolomics as one of the most rapidly growing technologies in the “-omics” field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients $ [ {\text{volume under ROC surface}}\;\left( {\text{VUS}} \right) = 0. 8 9 1 { }\left( { 9 5\,\% {\text{ CI }}0. 7 9 4- 0. 9 6 8} \right)]. $ We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and—despite all its current limitations—can deliver marker panels with high selectivity even in multi-class settings.     

Preconditioning of Microglia by α-Synuclein Strongly Affects the Response Induced by Toll-like Receptor (TLR) Stimulation

In recent years, it has become accepted that α-synuclein (αSyn) has a key role in the microglia-mediated neuroinflammation, which accompanies the development of Parkinson’s disease and other related disorders, such as Dementia with Lewy Bodies and Alzheimer’s disease. Nevertheless, the cellular and molecular mechanisms underlying its pathological actions, especially in the sporadic forms of the diseases, are not completely understood. Intriguingly, several epidemiological and animal model studies have revealed a link between certain microbial infections and the onset or progression of sporadic forms of these neurodegenerative disorders. In this work, we have characterized the effect of toll-like receptor (TLR) stimulation on primary murine microglial cultures and analysed the impact of priming cells with extracellular wild-type (Wt) αSyn on the subsequent TLR stimulation of cells with a set of TLR ligands. By assaying key interleukins and chemokines we report that specific stimuli, in particular Pam3Csk4 (Pam3) and single-stranded RNA40 (ssRNA), can differentially affect the TLR2/1- and TLR7-mediated responses of microglia when pre-conditioned with αSyn by augmenting IL-6, MCP-1/CCL2 or IP-10/CXCL10 secretion levels. Furthermore, we report a skewing of αSyn-primed microglia stimulated with ssRNA (TLR7) or Pam3 (TLR2/1) towards intermediate but at the same time differential, M1/M2 phenotypes. Finally, we show that the levels and intracellular location of activated caspase-3 protein change significantly in αSyn-primed microglia after stimulation with these particular TLR agonists. Overall, we report a remarkable impact of non-aggregated αSyn pre-sensitization of microglia on TLR-mediated immunity, a phenomenon that could contribute to triggering the onset of sporadic α-synuclein-related neuropathologies.     

Use of environmental DNA to detect Eastern Sand Darter (Ammocrypta pellucida Putnam, 1863) in large Laurentian Great Lakes embayments

A single-species environmental DNA (eDNA) method was developed to sample for a small, benthic rare species, Eastern Sand Darter (Ammocrypta pellucida Putnam, 1863) in two large Lake Ontario embayments. Summer water sampling allowed for: (a) surveys of habitats (Wellers Bay) where traditional fish sampling gear could not be used; and, (b) a comparison between eDNA and seining-based detection probabilities at known occupied habitats (West Lake). In 2018, replicate (n = 3) 1 L water samples were collected from 90 Wellers Bay sites and 71 West Lake sites. A site-occupancy model, a hierarchical logistic regression model, was fitted to determine site occupancy, sample occupancy (presence of Eastern Sand Darter DNA in a water sample) and probability of detection (p) based on replicate quantitative polymerase chain reaction (qPCR) results for each water sample. Eastern Sand Darter was detected at 10 West Lake sites, but not from Wellers Bay. Mean site occupancy was 0.31 (0.12–0.70; 95% CLs), mean sample occupancy was 0.28 (0.09–0.58; 95% CLs), and mean detection probability in a subsample (i.e., successful qPCR amplification) given it was present was 0.40 (0.25–0.55; 95% CLs). While the eDNA method successfully detected Eastern Sand Darter from known occupied areas in West Lake, it was not more effective for assessing local site occupancy than traditional sampling methods, such as the seine.     

Adaptive seamless clinical trials using early outcomes for treatment or subgroup selection: Methods,simulation model and their implementation in R

Adaptive seamless designs combine confirmatory testing, a domain of phase III trials, with features such as treatment or subgroup selection, typically associated with phase II trials. They promise to increase the efficiency of development programmes of new drugs, for example, in terms of sample size and/or development time. It is well acknowledged that adaptive designs are more involved from a logistical perspective and require more upfront planning, often in the form of extensive simulation studies, than conventional approaches. Here, we present a framework for adaptive treatment and subgroup selection using the same notation, which links the somewhat disparate literature on treatment selection on one side and on subgroup selection on the other. Furthermore, we introduce a flexible and efficient simulation model that serves both designs. As primary endpoints often take a long time to observe, interim analyses are frequently informed by early outcomes. Therefore, all methods presented accommodate interim analyses informed by either the primary outcome or an early outcome. The R package asd , previously developed to simulate designs with treatment selection, was extended to include subgroup selection (so-called adaptive enrichment designs). Here, we describe the functionality of the R package asd and use it to present some worked-up examples motivated by clinical trials in chronic obstructive pulmonary disease and oncology. The examples both illustrate various features of the R package and provide insights into the operating characteristics of adaptive seamless studies.     

Interactions of fish,algae, and abiotic factors in a shallow,tropical pond

Protecting and restoring shallow tropical lakes and wetlands requires a knowledge of what shapes and controls algal dynamics and primary productivity in these systems. Algal community structure and composition can be regulated either through biotic or abiotic controls. Large-scale changes in fish populations can affect algal communities by altering food web dynamics and the physical and chemical properties of the aquatic environment. A reduction in fish biomass can lead to a reduction in algal biomass because of increased grazing by zooplankton and reduced availablity of nutrients. However, the omnivorous fish common in tropical systems often consume algae, and their reduction can increase algal biomass. There is a need for more information on the effect of fish removals/reductions in tropical systems. In a five-year study of a shallow, tropical pond in Hawaii, I investigated the water quality effects of tilapia removal following the occurrence of two natural fish die-offs. I describe the concurrent impacts of water-level fluctuations and the fish die-offs on the physical and chemical conditions of the pond and the subsequent changes in the algal community. Overall, nutrients, suspended sediment, organic matter, and algal biomass were significantly reduced and light availability significantly increased in the absence of tilapia.