Mediators of monocyte chemotaxis and matrix remodeling are associated with mortality and pulmonary fibroproliferation in patients with severe COVID-19.

Acute respiratory distress syndrome (ARDS) has a fibroproliferative phase that may be followed by pulmonary fibrosis. Pulmonary fibrosis following COVID-19 pneumonia has been described at autopsy and following lung transplantation. We hypothesized that protein mediators of tissue remodeling and monocyte chemotaxis are elevated in the plasma and endotracheal aspirates of critically ill patients with COVID-19 who subsequently develop features of pulmonary fibroproliferation. We enrolled COVID-19 patients admitted to the ICU with hypoxemic respiratory failure. (n = 195). Plasma was collected within 24h of ICU admission and at 7d. In mechanically ventilated patients, endotracheal aspirates (ETA) were collected. Protein concentrations were measured by immunoassay. We tested for associations between protein concentrations and respiratory outcomes using logistic regression adjusting for age, sex, treatment with steroids, and APACHE III score. In a subset of patients who had CT scans during hospitalization (n = 75), we tested for associations between protein concentrations and radiographic features of fibroproliferation. Among the entire cohort, plasma IL-6, TNF-α, CCL2, and Amphiregulin levels were significantly associated with in-hospital mortality. In addition, higher plasma concentrations of CCL2, IL-6, TNF-α, Amphiregulin, and CXCL12 were associated with fewer ventilator-free days. We identified 20/75 patients (26%) with features of fibroproliferation. Within 24h of ICU admission, no measured plasma proteins were associated with a fibroproliferative response. However, when measured 96h-128h after admission, Amphiregulin was elevated in those that developed fibroproliferation. ETAs were not correlated with plasma measurements and did not show any association with mortality, ventilator-free days (VFDs), or fibroproliferative response. This cohort study identifies proteins of tissue remodeling and monocyte recruitment are associated with in-hospital mortality, fewer VFDs, and radiographic fibroproliferative response. Measuring changes in these proteins over time may allow for early identification of patients with severe COVID-19 at risk for fibroproliferation.

Identification of biomarkers for COVID-19 associated secondary hemophagocytic lymphohistiocytosis.

OBJECTIVES: We aimed to define and validate novel biomarkers that could identify individuals with COVID-19 associated secondary hemophagocytic lymphohistiocytosis (sHLH) and to test whether fatalities due to COVID-19 in the presence of sHLH were associated with specific defects in the immune system. DESIGN: In two cohorts of adult patients presenting with COVID-19 in 2020 and 2021, clinical lab values and serum proteomics were assessed. Subjects identified as having sHLH were compared to those with COVID-19 without sHLH. Eight deceased patients defined as COVID-sHLH underwent genomic sequencing in order to identify variants in immune-related genes. SETTING: Two tertiary care hospitals in Seattle, Washington (Virginia Mason Medical Center and Harborview Medical Center). PATIENTS: 186 patients with COVID-19. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Nine percent of enrolled COVID-19 subjects met our defined criteria for sHLH. Using broad serum proteomic approaches (O-link and SomaScan), we identified three biomarkers for COVID-19 associated sHLH (soluble PD-L1, TNF-R1, and IL-18BP), supporting a role for proteins previously associated with other forms of sHLH (IL-18BP and sTNF-R1). We also identified novel biomarkers and pathways of COVID-sHLH, including sPD-L1 and the syntaxin pathway. We detected variants in several genes involved in immune responses in individuals with COVID-sHLH, including in DOCK8 and in TMPRSS15, suggesting that genetic alterations in immune-related genes may contribute to hyperinflammation and fatal outcomes in COVID-19. CONCLUSIONS: Biomarkers of COVID-19 associated sHLH, such as soluble PD-L1, and pathways, such as the syntaxin pathway, and variants in immune genes in these individuals, suggest critical roles for the immune response in driving sHLH in the context of COVID-19.

Immune markers of severe acute pancreatitis.

PURPOSE OF REVIEW: Acute pancreatitis is a common acute inflammatory disorder of the pancreas, and its incidence has been increasing worldwide. Approximately 10% of acute pancreatitis progresses to severe acute pancreatitis (SAP), which carries significant morbidity and mortality. Disordered immune response to pancreatic injury is regarded as a key event that mediates systemic injury in SAP. In this article, we review recent developments in immune biomarkers of SAP and future directions for research. RECENT FINDINGS: Given the importance of the NLRP3-inflammasome pathway in mediating systemic inflammatory response syndrome and systemic injury, recent studies have investigated associations of SAP with systemic levels of activators of NLRP3, such as the damage associated molecular patterns (DAMPs) for the first time in human SAP. For example, circulating levels of histones, mitochondrial DNAs, and cell free DNAs have been associated with SAP. A panel of mechanistically relevant immune markers (e.g., panel of Angiopoeitin-2, hepatocyte growth factor, interleukin-8 (IL-8), resistin and sTNF-α R1) carried higher predictive accuracies than existing clinical scores and individual immune markers. Of the cytokines with established relevance to SAP pathogenesis, phase 2 trials of immunotherapies, including tumor necrosis factor (TNF)-alpha inhibition and stimulation of IL-10 production, are underway to determine if altering the immunologic response can reduce the severity of acute pancreatitis (AP). SUMMARY: Circulating systemic levels of various DAMPs and a panel of immune markers that possibly reflect activities of different pathways that drive SAP appear promising as predictive biomarkers for SAP. But larger multicenter studies are needed for external validation. Studies investigating immune cellular pathways driving SAP using immunophenotyping techniques are scarce. Interdisciplinary efforts are also needed to bring some of the promising biomarkers to the bedside for validation and testing for clinical utility. Studies investigating the role of and characterization of altered gut-lymph and gut-microbiota in severe AP are needed.

PD-L1 and PD-1 Are Associated with Clinical Outcomes and Alveolar Immune Cell Activation in ARDS.

The relationship between the Programmed Death-Ligand 1 (PD-L1)/Programmed Death-1 (PD-1) pathway, lung inflammation, and clinical outcomes in acute respiratory distress syndrome (ARDS) is poorly understood. We sought to determine whether PD-L1/PD-1 in the lung or blood is associated with ARDS and associated severity. We measured soluble PD-L1 (sPD-L1) in plasma and lower respiratory tract samples (ARDS1 (n = 59) and ARDS2 (n = 78)) or plasma samples alone (ARDS3 (n = 149)) collected from subjects with ARDS and tested for associations with mortality using multiple regression. We used mass cytometry to measure PD-L1/PD-1 expression and intracellular cytokine staining in cells isolated from bronchoalveolar lavage fluid (BALF) (n = 18) and blood (n = 16) from critically-ill subjects with or without ARDS enrolled from a fourth cohort. Higher plasma levels of sPD-L1 were associated with mortality in ARDS1, ARDS2, and ARDS3. In contrast, higher levels of sPD-L1 in the lung were either not associated with mortality (ARDS2) or were associated with survival (ARDS1). Alveolar PD-1POS T cells had more intracellular cytokine staining compared with PD-1NEG T cells. Subjects without ARDS had a higher ratio of PD-L1POS alveolar macrophages to PD-1POS T cells compared with subjects with ARDS. We conclude that sPD-L1 may have divergent cellular sources and/or functions in the alveolar vs. blood compartments given distinct associations with mortality. Alveolar leukocyte subsets defined by PD-L1/PD-1 cell-surface expression have distinct cytokine secretion profiles, and the relative proportions of these subsets are associated with ARDS.

Germline-like TCR-α chains shared between autoreactive T cells in blood and pancreas.

Human type 1 diabetes (T1D) is caused by autoimmune attack on the insulin-producing pancreatic beta cells by islet antigen-reactive T cells. How human islet antigen-reactive (IAR) CD4+ memory T cells from peripheral blood affect T1D progression in the pancreas is poorly understood. Here, we aim to determine if IAR T cells in blood could be detected in pancreas. We identify paired αß (TRA/TRB) T cell receptors (TCRs) in IAR T cells from the blood of healthy, at-risk, new-onset, and established T1D donors, and measured sequence overlap with TCRs in pancreata from healthy, at risk and T1D organ donors. We report extensive TRA junction sharing between IAR T cells and pancreas-infiltrating T cells (PIT), with perfect-match or single-mismatch TRA junction amino acid sequences comprising ~29% total unique IAR TRA junctions (942/3,264). PIT-matched TRA junctions were largely public and enriched for TRAV41 usage, showing significant nucleotide sequence convergence, increased use of germline-encoded versus non-templated residues in epitope engagement, and a potential for cross-reactivity. Our findings thus link T cells with distinctive germline-like TRA chains in the peripheral blood with T cells in the pancreas.

Beyond Stages: Predicting Individual Time Dependent Risk for Type 1 Diabetes.

BACKGROUND: Essentially all individuals with multiple autoantibodies will develop clinical type 1 diabetes. Multiple AABs and normal glucose tolerance define Stage 1 diabetes; abnormal glucose tolerance defines Stage 2. However, the rate of progression within these stages is heterogeneous, necessitating personalized risk calculators to improve clinical implementation. METHODS: We developed 3 models using TrialNet's Pathway to Prevention data to accommodate the reality that not all risk variables are clinically available. The Small model included AAB status, fasting glucose, HbA1c and age, while the Medium and Large models added predictors of disease progression measured via oral glucose tolerance testing. FINDINGS: All models markedly improved granularity regarding personalized risk missing from current categories of stages of T1D. Model derived risk calculations are consistent with the expected reduction of risk with increasing age and increase in risk with higher glucose and lower insulin secretion, illustrating the suitability of the models. Adding glucose and insulin secretion data altered model predicted probabilities within Stages. In those with high 2-hour glucose, a high C-peptide markedly decreased predicted risk; lower C-peptide obviated the age-dependent risk of 2-hour glucose alone, providing a more nuanced estimate of rate of disease progression within Stage 2. CONCLUSIONS: While essentially all those with multiple AABs will develop type 1 diabetes, the rate of progression is heterogeneous and not explained by any individual single risk variable. The model-based probabilities developed here provide an adaptable personalized risk calculator to better inform decisions about how and when to monitor disease progression in clinical practice.

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review.

BACKGROUND: Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies. METHODS: We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment. RESULTS: Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation. CONCLUSIONS: Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.

Islet autoantibodies are markers found in the blood when insulin-producing cells in the pancreas become damaged and can be used to predict future development of type 1 diabetes. We evaluated published literature to determine whether characteristics of islet antibodies (type, levels, numbers) could improve prediction and help understand differences in how individuals with type 1 diabetes respond to treatments. We found existing evidence shows that islet autoantibody type and number are most useful to predict disease progression before diagnosis. In addition, the age when islet autoantibodies first appear strongly influences rate of progression. These findings provide important information for patients and care providers on how islet autoantibodies can be used to understand future type 1 diabetes development and to identify individuals who have the potential to benefit from intervention or prevention therapy.

Human inherited PD-L1 deficiency is clinically and immunologically less severe than PD-1 deficiency.

We previously reported two siblings with inherited PD-1 deficiency who died from autoimmune pneumonitis at 3 and 11 years of age after developing other autoimmune manifestations, including type 1 diabetes (T1D). We report here two siblings, aged 10 and 11 years, with neonatal-onset T1D (diagnosed at the ages of 1 day and 7 wk), who are homozygous for a splice-site variant of CD274 (encoding PD-L1). This variant results in the exclusive expression of an alternative, loss-of-function PD-L1 protein isoform in overexpression experiments and in the patients' primary leukocytes. Surprisingly, cytometric immunophenotyping and single-cell RNA sequencing analysis on blood leukocytes showed largely normal development and transcriptional profiles across lymphoid and myeloid subsets in the PD-L1-deficient siblings, contrasting with the extensive dysregulation of both lymphoid and myeloid leukocyte compartments in PD-1 deficiency. Our findings suggest that PD-1 and PD-L1 are essential for preventing early-onset T1D but that, unlike PD-1 deficiency, PD-L1 deficiency does not lead to fatal autoimmunity with extensive leukocytic dysregulation.

Abatacept increases T cell exhaustion in early RA individuals who carry HLA risk alleles.

Exhausted CD8 T cells (TEX) are associated with worse outcome in cancer yet better outcome in autoimmunity. Building on our past findings of increased TIGIT+KLRG1+ TEX with teplizumab therapy in type 1 diabetes (T1D), in the absence of treatment we found that the frequency of TIGIT+KLRG1+ TEX is stable within an individual but differs across individuals in both T1D and healthy control (HC) cohorts. This TIGIT+KLRG1+ CD8 TEX population shares an exhaustion-associated EOMES gene signature in HC, T1D, rheumatoid arthritis (RA), and cancer subjects, expresses multiple inhibitory receptors, and is hyporesponsive in vitro, together suggesting co-expression of TIGIT and KLRG1 may broadly define human peripheral exhausted cells. In HC and RA subjects, lower levels of EOMES transcriptional modules and frequency of TIGIT+KLRG1+ TEX were associated with RA HLA risk alleles (DR0401, 0404, 0405, 0408, 1001) even when considering disease status and cytomegalovirus (CMV) seropositivity. Moreover, the frequency of TIGIT+KLRG1+ TEX was significantly increased in RA HLA risk but not non-risk subjects treated with abatacept (CTLA4Ig). The DR4 association and selective modulation with abatacept suggests that therapeutic modulation of TEX may be more effective in DR4 subjects and TEX may be indirectly influenced by cellular interactions that are blocked by abatacept.

Testing a new platform to screen disease-modifying therapy in type 1 diabetes.

Studies of new therapies to preserve insulin secretion in early type 1 diabetes require several years to recruit eligible subjects and to see a treatment effect; thus, there is interest in alternative study designs to speed this process. Most people with longstanding type 1 diabetes no longer secrete insulin. However, studies from pancreata of those with longstanding T1D show that beta cells staining for insulin can persist for decades after diagnosis, and this is paralleled in work showing proinsulin secretion in individuals with longstanding disease; collectively this suggests that there is a reserve of alive but "sleeping" beta cells. Here, we designed a novel clinical trial platform to test whether a short course of therapy with an agent known to have effects in type 1 diabetes with residual endogenous insulin could transiently induce insulin secretion in those who no longer produce insulin. A therapy that transiently "wakes up" sleeping beta cells might be tested next in a fully powered trial in those with endogenous insulin secretion. In this three-arm non-randomized pilot study, we tested three therapies known to impact disease: two beta-cell supportive agents, liraglutide and verapamil, and an immunomodulatory agent, golimumab. The golimumab treated arm was not fully enrolled due to uncertainties about immunotherapy during the COVID-19 pandemic. Participants had mixed-meal tolerance test (MMTT)-stimulated C-peptide below the quantitation limit (<0.02 ng/mL) at enrollment and received 8 to 12 weeks of therapy. At the completion of therapy, none of the individuals achieved the primary outcome of MMTT-stimulated C-peptide ≥ 0.02 ng/mL. An exploratory outcome of the verapamil arm was MRI-assessed pancreas size, diffusion, and longitudinal relaxation time, which showed repeatability of these measures but no treatment effect. The liraglutide and golimumab arms were registered on clinicaltrials.gov under accession number NCT03632759 and the verapamil arm under accession number NCT05847413. Trail registration: Protocols are registered in ClinicalTrials.gov under accession numbers NCT03632759 and NCT05847413.

A standardized metric to enhance clinical trial design and outcome interpretation in type 1 diabetes.

The use of a standardized outcome metric enhances clinical trial interpretation and cross-trial comparison. If a disease course is predictable, comparing modeled predictions with outcome data affords the precision and confidence needed to accelerate precision medicine. We demonstrate this approach in type 1 diabetes (T1D) trials aiming to preserve endogenous insulin secretion measured by C-peptide. C-peptide is predictable given an individual's age and baseline value; quantitative response (QR) adjusts for these variables and represents the difference between the observed and predicted outcome. Validated across 13 trials, the QR metric reduces each trial's variance and increases statistical power. As smaller studies are especially subject to random sampling variability, using QR as the outcome introduces alternative interpretations of previous clinical trial results. QR can provide model-based estimates that quantify whether individuals or groups did better or worse than expected. QR also provides a purer metric to associate with biomarker measurements. Using data from more than 1300 participants, we demonstrate the value of QR in advancing disease-modifying therapy in T1D. QR applies to any disease where outcome is predictable by pre-specified baseline covariates, rendering it useful for defining responders to therapy, comparing therapeutic efficacy, and understanding causal pathways in disease.

Self-reactive germline-like TCR alpha chains shared between blood and pancreas.

Human islet antigen reactive CD4 + memory T cells (IAR T cells) from peripheral blood have been studied extensively for their role in the pathogenesis of autoimmune type 1 diabetes (T1D). However, IAR T cells are rare, and it remains poorly understood how they affect T1D progression in the pancreas. Using single cell RNA-sequencing coupled with a multiplexed activation induced marker (AIM) enrichment assay, we identified paired TCR alpha/beta (TRA/TRB) T cell receptors (TCRs) in IAR T cells from the blood of healthy, at-risk, new onset, and established T1D donors. Using TCR sequences as barcodes, we measured infiltration of IAR T cells from blood into pancreas of organ donors with and without T1D. We detected extensive TCR sharing between IAR T cells from peripheral blood and pancreatic infiltrating T cells (PIT), with perfectly matched or single mismatched TRA junctions and J gene regions, comprising ~ 34% of unique IAR TCRs. PIT-matching IAR T cells had public TRA chains that showed increased use of germline-encoded residues in epitope engagement and a propensity for cross-reactivity. The link with T cells in the pancreas implicates autoreactive IAR T cells with shared TRA junctions and increased levels in blood with the prediabetic and new onset phases of T1D progression.

Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review.

BACKGROUND: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification. METHODS: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. RESULTS: We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings. CONCLUSIONS: While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.

Type 1 diabetes (T1D) is a condition that results from the destruction of a type of cell in the pancreas that produces the hormone insulin, leading to lifelong dependence on insulin injections. T1D prevention remains a challenging goal, largely due to the immense variability in disease processes and progression. Therapies tested to date in medical research settings (clinical trials) work only in a subset of individuals, highlighting the need for more tailored prevention approaches. We reviewed clinical trials of therapies targeting the disease process in T1D. While the overall quality of trials was high, studies testing individual features affecting responses to treatments were low. This review reveals an important need to carefully plan high-quality analyses of features that affect treatment response in T1D, to ensure that tailored approaches may one day be applied to clinical practice.

Trimodal single-cell profiling reveals a novel pediatric CD8αα+ T cell subset and broad age-related molecular reprogramming across the T cell compartment.

Age-associated changes in the T cell compartment are well described. However, limitations of current single-modal or bimodal single-cell assays, including flow cytometry, RNA-seq (RNA sequencing) and CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), have restricted our ability to deconvolve more complex cellular and molecular changes. Here, we profile >300,000 single T cells from healthy children (aged 11-13 years) and older adults (aged 55-65 years) by using the trimodal assay TEA-seq (single-cell analysis of mRNA transcripts, surface protein epitopes and chromatin accessibility), which revealed that molecular programming of T cell subsets shifts toward a more activated basal state with age. Naive CD4+ T cells, considered relatively resistant to aging, exhibited pronounced transcriptional and epigenetic reprogramming. Moreover, we discovered a novel CD8αα+ T cell subset lost with age that is epigenetically poised for rapid effector responses and has distinct inhibitory, costimulatory and tissue-homing properties. Together, these data reveal new insights into age-associated changes in the T cell compartment that may contribute to differential immune responses.

Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes.

Genome-wide association studies have identified numerous loci with allelic associations to Type 1 Diabetes (T1D) risk. Most disease-associated variants are enriched in regulatory sequences active in lymphoid cell types, suggesting that lymphocyte gene expression is altered in T1D. Here we assay gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4+/CD25+ regulatory T cells (Treg) and memory CD4+/CD25- T cells, using a splicing event-based approach to characterize tissue-specific transcriptomes. Limited differences in isoform usage between T1D cases and controls are observed in memory CD4+/CD25- T-cells. In Tregs, 402 genes demonstrate differences in isoform usage between cases and controls, particularly RNA recognition and splicing factor genes. Many of these genes are regulated by the variable inclusion of exons that can trigger nonsense mediated decay. Our results suggest that dysregulation of gene expression, through shifts in alternative splicing in Tregs, contributes to T1D pathophysiology.

Islet-autoreactive CD4+ T cells are linked with response to alefacept in type 1 diabetes.

Variation in the preservation of ß cell function in clinical trials in type 1 diabetes (T1D) has emphasized the need to define biomarkers to predict treatment response. The T1DAL trial targeted T cells with alefacept (LFA-3-Ig) and demonstrated C-peptide preservation in approximately 30% of new-onset T1D individuals. We analyzed islet antigen-reactive (IAR) CD4+ T cells in PBMC samples collected prior to treatment from alefacept- and placebo-treated individuals using flow cytometry and single-cell RNA sequencing. IAR CD4+ T cells at baseline had heterogeneous phenotypes. Transcript profiles formed phenotypic clusters of cells along a trajectory based on increasing maturation and activation, and T cell receptor (TCR) chains showed clonal expansion. Notably, the frequency of IAR CD4+ T cells with a memory phenotype and a unique transcript profile (cluster 3) were inversely correlated with C-peptide preservation in alefacept-treated, but not placebo-treated, individuals. Cluster 3 cells had a proinflammatory phenotype characterized by expression of the transcription factor BHLHE40 and the cytokines GM-CSF and TNF-α, and shared TCR chains with effector memory-like clusters. Our results suggest IAR CD4+ T cells as a potential baseline biomarker of response to therapies targeting the CD2 pathway and warrant investigation for other T cell-related therapies.

OGTT Metrics Surpass Continuous Glucose Monitoring Data for T1D Prediction in Multiple-Autoantibody-Positive Individuals.

CONTEXT: The value of continuous glucose monitoring (CGM) for monitoring autoantibody (AAB)-positive individuals in clinical trials for progression of type 1 diabetes (T1D) is unknown. OBJECTIVE: Compare CGM with oral glucose tolerance test (OGTT)-based metrics in prediction of T1D. METHODS: At academic centers, OGTT and CGM data from multiple-AAB relatives were evaluated for associations with T1D diagnosis. Participants were multiple-AAB-positive individuals in a TrialNet Pathway to Prevention (TN01) CGM ancillary study (n = 93). The intervention was CGM for 1 week at baseline, 6 months, and 12 months. Receiver operating characteristic (ROC) curves of CGM and OGTT metrics for prediction of T1D were analyzed. RESULTS: Five of 7 OGTT metrics and 29/48 CGM metrics but not HbA1c differed between those who subsequently did or did not develop T1D. ROC area under the curve (AUC) of individual CGM values ranged from 50% to 69% and increased when adjusted for age and AABs. However, the highest-ranking metrics were derived from OGTT: 4/7 with AUC ∼80%. Compared with adjusted multivariable models using CGM data, OGTT-derived variables, Index60 and DPTRS (Diabetes Prevention Trial-Type 1 Risk Score), had higher discriminative ability (higher ROC AUC and positive predictive value with similar negative predictive value). CONCLUSION: Every 6-month CGM measures in multiple-AAB-positive individuals are predictive of subsequent T1D, but less so than OGTT-derived variables. CGM may have feasibility advantages and be useful in some settings. However, our data suggest there is insufficient evidence to replace OGTT measures with CGM in the context of clinical trials.

Measuring anti-islet autoimmunity in mouse and human by profiling peripheral blood antigen-specific CD4 T cells.

The endocrine pancreas is one of the most inaccessible organs of the human body. Its autoimmune attack leads to type 1 diabetes (T1D) in a genetically susceptible population and a lifelong need for exogenous insulin replacement. Monitoring disease progression by sampling peripheral blood would provide key insights into T1D immune-mediated mechanisms and potentially change preclinical diagnosis and the evaluation of therapeutic interventions. This effort has been limited to the measurement of circulating anti-islet antibodies, which despite a recognized diagnostic value, remain poorly predictive at the individual level for a fundamentally CD4 T cell-dependent disease. Here, peptide-major histocompatibility complex tetramers were used to profile blood anti-insulin CD4 T cells in mice and humans. While percentages of these were not directly informative, the state of activation of anti-insulin T cells measured by RNA and protein profiling was able to distinguish the absence of autoimmunity versus disease progression. Activated anti-insulin CD4 T cell were detected not only at time of diagnosis but also in patients with established disease and in some at-risk individuals. These results support the concept that antigen-specific CD4 T cells might be used to monitor autoimmunity in real time. This advance can inform our approach to T1D diagnosis and therapeutic interventions in the preclinical phase of anti-islet autoimmunity.

Technical Validation and Utility of an HLA Class II Tetramer Assay for Type 1 Diabetes: A Multicenter Study.

CONTEXT: Validated assays to measure autoantigen-specific T-cell frequency and phenotypes are needed for assessing the risk of developing diabetes, monitoring disease progression, evaluating responses to treatment, and personalizing antigen-based therapies. OBJECTIVE: Toward this end, we performed a technical validation of a tetramer assay for HLA-DRA-DRB1*04:01, a class II allele that is strongly associated with susceptibility to type 1 diabetes (T1D). METHODS: HLA-DRA-DRB1*04:01-restricted T cells specific for immunodominant epitopes from islet cell antigens GAD65, IGRP, preproinsulin, and ZnT8, and a reference influenza epitope, were enumerated and phenotyped in a single staining tube with a tetramer assay. Single and multicenter testing was performed, using a clone-spiked specimen and replicate samples from T1D patients, with a target coefficient of variation (CV) less than 30%. The same assay was applied to an exploratory cross-sectional sample set with 24 T1D patients to evaluate the utility of the assay. RESULTS: Influenza-specific T-cell measurements had mean CVs of 6% for the clone-spiked specimen and 11% for T1D samples in single-center testing, and 20% and 31%, respectively, for multicenter testing. Islet-specific T-cell measurements in these same samples had mean CVs of 14% and 23% for single-center and 23% and 41% for multicenter testing. The cross-sectional study identified relationships between T-cell frequencies and phenotype and disease duration, sex, and autoantibodies. A large fraction of the islet-specific T cells exhibited a naive phenotype. CONCLUSION: Our results demonstrate that the assay is reproducible and useful to characterize islet-specific T cells and identify correlations between T-cell measures and clinical traits.