Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation

Lactobacillus plantarum 299v probiotic supplementation in men with stable coronary artery disease suppresses systemic inflammation

Recent trials demonstrate that systemic anti-inflammatory therapy reduces cardiovascular events in coronary artery disease (CAD) patients. We recently demonstrated Lactobacillus plantarum 299v (Lp299v) supplementation improved vascular endothelial function in men with stable CAD. Whether this favorable effect is in part due to anti-inflammatory action remains unknown. Testing this hypothesis, we exposed plasma obtained before and after Lp299v supplementation from these subjects to a healthy donor's PBMCs and measured differences in the PBMC transciptome, performed gene ontological analyses, and compared Lp299v-induced transcriptome changes with changes in vascular function. Daily alcohol users (DAUs) (n = 4) had a significantly different response to Lp299v and were separated from the main analyses. Non-DAUs- (n = 15) showed improved brachial flow-mediated dilation (FMD) and reduced circulating IL-8, IL-12, and leptin. 997 genes were significantly changed. I.I.com decreased (1.01 ± 0.74 vs. 0.22 ± 0.51; P < 0.0001), indicating strong anti-inflammatory effects. Pathway analyses revealed downregulation of IL-1β, interferon-stimulated pathways, and toll-like receptor signaling, and an increase in regulator T-cell (Treg) activity. Reductions in GBP1, JAK2, and TRAIL expression correlated with improved FMD. In non-DAU men with stable CAD, post-Lp299v supplementation plasma induced anti-inflammatory transcriptome changes in human PBMCs that could benefit CAD patients. Future studies should delineate changes in circulating metabolites responsible for these effects.

A composite immune signature parallels disease progression across T1D subjects

At diagnosis, most people with type 1 diabetes (T1D) produce measurable levels of endogenous insulin, but the rate at which insulin secretion declines is heterogeneous. To explain this heterogeneity, we sought to identify a composite signature predictive of insulin secretion, using a collaborative assay evaluation and analysis pipeline that incorporated multiple cellular and serum measures reflecting β cell health and immune system activity. The ability to predict decline in insulin secretion would be useful for patient stratification for clinical trial enrollment or therapeutic selection. Analytes from 12 qualified assays were measured in shared samples from subjects newly diagnosed with T1D. We developed a computational tool (DIFAcTO, Data Integration Flexible to Account for different Types of data and Outcomes) to identify a composite panel associated with decline in insulin secretion over 2 years following diagnosis. DIFAcTO uses multiple filtering steps to reduce data dimensionality, incorporates error estimation techniques including cross-validation and sensitivity analysis, and is flexible to assay type, clinical outcome, and disease setting. Using this novel analytical tool, we identified a panel of immune markers that, in combination, are highly associated with loss of insulin secretion. The methods used here represent a potentially novel process for identifying combined immune signatures that predict outcomes relevant for complex and heterogeneous diseases like T1D.

Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study

Immune analytes have been widely tested in efforts to understand the heterogeneity of disease progression, risk, and therapeutic responses in type 1 diabetes (T1D). The future clinical utility of such analytes as biomarkers depends on their technical and biological variability, as well as their correlation with clinical outcomes. To assess the variability of a panel of 91 immune analytes, we conducted a prospective study of adults with T1D (<3 years from diagnosis), at 9–10 visits over 1 year. Autoantibodies and frequencies of T-cell, natural killer cell, and myeloid subsets were evaluated; autoreactive T-cell frequencies and function were also measured. We calculated an intraclass correlation coefficient (ICC) for each marker, which is a relative measure of between- and within-subject variability. Of the 91 analytes tested, we identified 35 with high between- and low within-subject variability, indicating their potential ability to be used to stratify subjects. We also provide extensive data regarding technical variability for 64 of the 91 analytes. To pilot the concept that ICC can be used to identify analytes that reflect biological outcomes, the association between each immune analyte and C-peptide was also evaluated using partial least squares modeling. CD8 effector memory T-cell (CD8 EM) frequency exhibited a high ICC and a positive correlation with C-peptide, which was also seen in an independent dataset of recent-onset T1D subjects. More work is needed to better understand the mechanisms underlying this relationship. Here we find that there are a limited number of technically reproducible immune analytes that also have a high ICC. We propose the use of ICC to define within- and between-subject variability and measurement of technical variability for future biomarker identification studies. Employing such a method is critical for selection of analytes to be tested in the context of future clinical trials aiming to understand heterogeneity in disease progression and response to therapy.

Standardizing T-Cell Biomarkers in Type 1 Diabetes: Challenges and Recent Advances

Type 1 diabetes (T1D) results from the progressive destruction of pancreatic β-cells in a process mediated primarily by T lymphocytes. The T1D research community has made dramatic progress in understanding the genetic basis of the disease as well as in the development of standardized autoantibody assays that inform both disease risk and progression. Despite these advances, there remains a paucity of robust and accepted biomarkers that can effectively inform on the activity of T cells during the natural history of the disease or in response to treatment. In this article, we discuss biomarker development and validation efforts for evaluation of T-cell responses in patients with and at risk for T1D as well as emerging technologies. It is expected that with systematic planning and execution of a well-conceived biomarker development pipeline, T-cell-related biomarkers would rapidly accelerate disease progression monitoring efforts and the evaluation of intervention therapies in T1D.

Treg gene signatures predict and measure type 1 diabetes trajectory

BACKGROUND

Multiple therapeutic strategies to restore immune regulation and slow type 1 diabetes (T1D) progression are in development and testing. A major challenge has been defining biomarkers to prospectively identify subjects likely to benefit from immunotherapy and/or measure intervention effects. We previously found that, compared with healthy controls, Tregs from children with new-onset T1D have an altered Treg gene signature (TGS), suggesting that this could be an immunoregulatory biomarker.

METHODS

nanoString was used to assess the TGS in sorted Tregs (CD4+CD25hiCD127lo) or peripheral blood mononuclear cells (PBMCs) from individuals with T1D or type 2 diabetes, healthy controls, or T1D recipients of immunotherapy. Biomarker discovery pipelines were developed and applied to various sample group comparisons.

RESULTS

Compared with controls, the TGS in isolated Tregs or PBMCs was altered in adult new-onset and cross-sectional T1D cohorts, with sensitivity or specificity of biomarkers increased by including T1D-associated SNPs in algorithms. The TGS was distinct in T1D versus type 2 diabetes, indicating disease-specific alterations. TGS measurement at the time of T1D onset revealed an algorithm that accurately predicted future rapid versus slow C-peptide decline, as determined by longitudinal analysis of placebo arms of START and T1DAL trials. The same algorithm stratified participants in a phase I/II clinical trial of ustekinumab (αIL-12/23p40) for future rapid versus slow C-peptide decline.

CONCLUSION

These data suggest that biomarkers based on measuring TGSs could be a new approach to stratify patients and monitor autoimmune activity in T1D.

FUNDING

JDRF (1-PNF-2015-113-Q-R, 2-PAR-2015-123-Q-R, 3-SRA-2016-209-Q-R, 3-PDF-2014-217-A-N), the JDRF Canadian Clinical Trials Network, the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (UM1AI109565 and FY15ITN168), and BCCHRI.

Innate immune activity as a predictor of persistent insulin secretion and association with responsiveness to CTLA4-Ig treatment in recent-onset type 1 diabetes

AIMS/HYPOTHESIS

The study aimed to determine whether discrete subtypes of type 1 diabetes exist, based on immunoregulatory profiles at clinical onset, as this has significant implications for disease treatment and prevention as well as the design and analysis of clinical trials.

METHODS

Using a plasma-based transcriptional bioassay and a gene-ontology-based scoring algorithm, we examined local participants from the Children's Hospital of Wisconsin and conducted an ancillary analysis of TrialNet CTLA4-Ig trial (TN-09) participants.

RESULTS

The inflammatory/regulatory balance measured during the post-onset period was highly variable. Notably, a significant inverse relationship was identified between baseline innate inflammatory activity and stimulated C-peptide AUC measured at 3, 6, 12, 18 and 24 months post onset among placebo-treated individuals (p ≤ 0.015). Further, duration of persistent insulin secretion was negatively related to baseline inflammation (p ≤ 0.012) and positively associated with baseline abundance of circulating activated regulatory T cells (CD4⁺/CD45RA^-/FOXP3^high; p = 0.016). Based on these findings, data from participants treated with CTLA4-Ig were stratified by inflammatory activity at onset; in this way, we identified pathways and transcripts consistent with inhibition of T cell activation and enhanced immunoregulation. Variance among baseline plasma-induced signatures of TN-09 participants was further examined with weighted gene co-expression network analysis and related to clinical metrics. Four age-independent subgroups were identified that differed in terms of baseline innate inflammatory/regulatory bias, rate of C-peptide decline and response to CTLA4-Ig treatment.

CONCLUSIONS/INTERPRETATION

These data support the existence of multiple type 1 diabetes subtypes characterised by varying levels of baseline innate inflammation that are associated with the rate of C-peptide decline.

DATA AVAILABILITY

Gene expression data files are publicly available through the National Center for Biotechnology Information Gene Expression Omnibus (accession number GSE102234).

NETosis-associated serum biomarkers are reduced in type 1 diabetes in association with neutrophil count

As the immune pathways involved in the pathogenesis of type 1 diabetes (T1D) are not fully understood, biomarkers implicating novel mechanisms of disease are of great interest and call for independent evaluation. Recently, it was reported that individuals with T1D display dramatic elevations in circulating components of neutrophil extracellular traps (NETs), indicating a potential role for NETosis in T1D. Our aim was to evaluate further the potential of NET-associated proteins as novel circulating biomarkers in T1D. We tested serum from subjects with T1D (n = 44) with a median age of 26·5 years and a median duration of 2·2 years, along with 38 age-matched controls. T1D subjects did not show elevations in either neutrophil elastase (NE) or proteinase 3 (PR3), as reported previously. In fact, both NE and PR3 levels were reduced significantly in T1D subjects, particularly in subjects within 3 years of diagnosis, consistent with the known reduction in neutrophil counts in recent-onset T1D. Indeed, levels of both NE and PR3 correlated with absolute neutrophil counts. Therefore, while not ruling out potential local or transient spikes in NETosis activity, the levels of these serum markers do not support a role for systemically elevated NETosis in the T1D population we studied. Rather, a modest reduction in these markers may reflect other important aspects of disease activity associated with reduced neutrophil numbers.