Proteome Mapping of the Human Pancreatic Islet Microenvironment Reveals Endocrine-Exocrine Signaling Sphere of Influence.

The need for a clinically accessible method with the ability to match protein activity within heterogeneous tissues is currently unmet by existing technologies. Our proteomics sample preparation platform, named microPOTS (Microdroplet Processing in One pot for Trace Samples), can be used to measure relative protein abundance in micron-scale samples alongside the spatial location of each measurement, thereby tying biologically interesting proteins and pathways to distinct regions. However, given the smaller pixel/voxel number and amount of tissue measured, standard mass spectrometric analysis pipelines have proven inadequate. Here we describe how existing computational approaches can be adapted to focus on the specific biological questions asked in spatial proteomics experiments. We apply this approach to present an unbiased characterization of the human islet microenvironment comprising the entire complex array of cell types involved while maintaining spatial information and the degree of the islet's sphere of influence. We identify specific functional activity unique to the pancreatic islet cells and demonstrate how far their signature can be detected in the adjacent tissue. Our results show that we can distinguish pancreatic islet cells from the neighboring exocrine tissue environment, recapitulate known biological functions of islet cells, and identify a spatial gradient in the expression of RNA processing proteins within the islet microenvironment.

Imaging abnormalities of the pancreas in diabetes: implications for diagnosis and treatment.

PURPOSE OF REVIEW: Radiographic imaging of the pancreas has drawn recent interest as pancreas volume may serve as a biomarker in identifying the likelihood of diabetes development, subtyping diabetes, and identifying prognostic indicators of poor ultimate outcomes. In this review, the role of pancreas imaging is discussed in various forms of diabetes including type 1 diabetes (T1D), type 2 diabetes (T2D), and diabetes of the exocrine pancreas, particularly diabetes following acute or chronic pancreatitis. RECENT FINDINGS: Recent literature of quantitative pancreatic imaging correlating with various forms of diabetes was reviewed. Imaging-derived pancreas volumes are lower in individuals with diabetes, in particular those with T1D. Additionally, morphologic changes, enhancement characteristics, fat content, and MRI signal changes have been observed in different diabetes subtypes. These characteristics, as well as potential confounding variables, are reviewed. Additionally, future areas of research in MRI, CT radiomics, and pancreatitis-related imaging predictors of diabetes are discussed. SUMMARY: Increased understanding of pancreas imaging features which predict diabetes and gauge prognosis has the potential to identify at-risk individuals and will become increasingly important in diabetes care. This article reviews the current knowledge of common pancreas imaging features as well as future directions of ongoing research in diabetes imaging.

Image-Based Machine Learning Algorithms for Disease Characterization in the Human Type 1 Diabetes Pancreas.

Emerging data suggest that type 1 diabetes affects not only the ß-cell-containing islets of Langerhans, but also the surrounding exocrine compartment. Using digital pathology, machine learning algorithms were applied to high-resolution, whole-slide images of human pancreata to determine whether the tissue composition in individuals with or at risk for type 1 diabetes differs from those without diabetes. Transplant-grade pancreata from organ donors were evaluated from 16 nondiabetic autoantibody-negative controls, 8 nondiabetic autoantibody-positive subjects with increased type 1 diabetes risk, and 19 persons with type 1 diabetes (0 to 12 years' duration). HALO image analysis algorithms were implemented to compare architecture of the main pancreatic duct as well as cell size, density, and area of acinar, endocrine, ductal, and other nonendocrine, nonexocrine tissues. Type 1 diabetes was found to affect exocrine area, acinar cell density, and size, whereas the type of difference correlated with the presence or absence of insulin-positive cells remaining in the pancreas. These changes were not observed before disease onset, as indicated by modeling cross-sectional data from pancreata of autoantibody-positive subjects and those diagnosed with type 1 diabetes. These data provide novel insights into anatomic differences in type 1 diabetes pancreata and demonstrate that machine learning can be adapted for the evaluation of disease processes from cross-sectional data sets.

Organisation of the human pancreas in health and in diabetes.

For much of the last century, our knowledge regarding the pancreas in type 1 and type 2 diabetes was largely derived from autopsy studies of individuals with these disorders or investigations utilising rodent models of either disease. While many important insights emanated from these efforts, the mode for investigation has increasingly seen change due to the availability of transplant-quality organ-donor tissues, improvements in pancreatic imaging, advances in metabolic assessments of living patients, genetic analyses, technological advances for laboratory investigation and more. As a result, many long-standing notions regarding the role for and the changes that occur in the pancreas in individuals with these disorders have come under question, while, at the same time, new issues (e.g., beta cell persistence, disease heterogeneity, exocrine contributions) have arisen. In this article, we will consider the vital role of the pancreas in human health and physiology, including discussion of its anatomical features and dual (exocrine and endocrine) functions. Specifically, we convey changes that occur in the pancreas of those with either type 1 or type 2 diabetes, with careful attention to the facets that may contribute to the pathogenesis of either disorder. Finally, we discuss the emerging unknowns with the belief that understanding the role of the pancreas in type 1 and type 2 diabetes will lead to improvements in disease diagnosis, understanding of disease heterogeneity and optimisation of treatments at a personalised level. Graphical abstract.

Exocrine Pancreas Dysfunction in Type 1 Diabetes.

OBJECTIVE: Type 1 diabetes (T1D) is characterized by autoimmune ß-cell destruction, but exocrine pancreas abnormalities may also play a role in the disease pathophysiology. Herein, we review the current evidence of exocrine damage in T1D and discuss its underlying pathophysiology, clinical evaluation, and treatment. METHOD: Extensive literature search was performed for "type 1 diabetes" and "exocrine dysfunction" on PubMed and Google Scholar databases. RESULTS: T1D pancreata are significantly smaller than controls, both in weight and volume. T cells, dendritic cells, neutrophils, and products of complement activation are seen in T1D exocrine tissues. Exocrine pancreas fibrosis, arteriosclerosis, fatty infiltration, and acinar atrophy are also observed on histology. Pancreatic exocrine insufficiency (PEI) can be assessed through direct exocrine testing, fecal elastase concentration, and measurement of serum exocrine enzymes. The prevalence of PEI in T1D varies by modality and study but is consistently greater than controls. The clinical relevance of PEI in T1D is debatable, as many patients with laboratory evidence of PEI are asymptomatic. However, in PEI-symptomatic patients reported benefits of pancreatic enzyme replacement therapy (PERT) include relief of gastrointestinal symptoms, improved quality of life, better glycemic control, and optimal nutrition. CONCLUSION: Exocrine pancreas abnormalities often occur in T1D. Whether exocrine dysfunction occurs simultaneously with ß-cell destruction, as a result of ß-cell loss, or as a combination of both remains to be definitively answered. In T1D with gastrointestinal complaints, PEI should be evaluated, usually via fecal elastase measurements. PERT is recommended for T1D patients with symptoms and laboratory evidence of PEI. ABBREVIATIONS: AAb+ = autoantibody positive; AAb- = autoantibody negative; FEC = fecal elastase concentration; PEI = pancreatic exocrine insufficiency; PERT = pancreatic enzyme replacement therapy; PP = pancreatic polypep-tide; T1D = type 1 diabetes.

The Role of Accessory Cells in Islet Homeostasis.

PURPOSES OF REVIEW: Scattered throughout the pancreas, the endocrine islets rely on neurovascular support for signal relay to regulate hormone secretion and for maintaining tissue homeostasis. The islet accessory cells (or components) of neurovascular tissues include the endothelial cells, pericytes, smooth muscle cells, neurons (nerve fibers), and glia. Research results derived from experimental diabetes and islet transplantation indicate that the accessory cells are reactive in islet injury and can affect islet function and homeostasis in situ or in an ectopic environment. RECENT FINDINGS: Recent advances in cell labeling and tissue imaging have enabled investigation of islet accessory cells to gain insights into their network structures, functions, and remodeling in disease. It has become clear that in diabetes, the islet neurovascular tissues are not just bystanders damaged in neuropathy and vascular complications; rather, they participate in islet remodeling in response to changes in the microenvironment. Because of the fundamental differences between humans and animal models in neuroinsular cytoarchitecture and cell proliferation, examination of islet accessory cells in clinical specimens and donor pancreases warrants further attention.

5 Year Expression and Neutrophil Defect Repair after Gene Therapy in Alpha-1 Antitrypsin Deficiency.

Alpha-1 antitrypsin deficiency is a monogenic disorder resulting in emphysema due principally to the unopposed effects of neutrophil elastase. We previously reported achieving plasma wild-type alpha-1 antitrypsin concentrations at 2.5%-3.8% of the purported therapeutic level at 1 year after a single intramuscular administration of recombinant adeno-associated virus serotype 1 alpha-1 antitrypsin vector in alpha-1 antitrypsin deficient patients. We analyzed blood and muscle for alpha-1 antitrypsin expression and immune cell response. We also assayed previously reported markers of neutrophil function known to be altered in alpha-1 antitrypsin deficient patients. Here, we report sustained expression at 2.0%-2.5% of the target level from years 1-5 in these same patients without any additional recombinant adeno-associated virus serotype-1 alpha-1 antitrypsin vector administration. In addition, we observed partial correction of disease-associated neutrophil defects, including neutrophil elastase inhibition, markers of degranulation, and membrane-bound anti-neutrophil antibodies. There was also evidence of an active T regulatory cell response (similar to the 1 year data) and an exhausted cytotoxic T cell response to adeno-associated virus serotype-1 capsid. These findings suggest that muscle-based alpha-1 antitrypsin gene replacement is tolerogenic and that stable levels of M-AAT may exert beneficial neutrophil effects at lower concentrations than previously anticipated.

Beyond the brain: disrupted in schizophrenia 1 regulates pancreatic ß-cell function via glycogen synthase kinase-3ß.

Individuals with schizophrenia and their first-degree relatives have higher rates of type 2 diabetes (T2D) than the general population (18-30 vs. 1.2-6.3%), independent of body mass index and antipsychotic medication, suggesting shared genetic components may contribute to both diseases. The cause of this association remains unknown. Mutations in disrupted in schizophrenia 1 (DISC1) increase the risk of developing psychiatric disorders [logarithm (base 10) of odds = 7.1]. Here, we identified DISC1 as a major player controlling pancreatic ß-cell proliferation and insulin secretion via regulation of glycogen synthase kinase-3ß (GSK3ß). DISC1 expression was enriched in developing mouse and human pancreas and adult ß- and ductal cells. Loss of DISC1 function, through siRNA-mediated depletion or expression of a dominant-negative truncation that models the chromosomal translocation of human DISC1 in schizophrenia, resulted in decreased ß-cell proliferation (3 vs. 1%; P < 0.01), increased apoptosis (0.1 vs. 0.6%; P < 0.01), and glucose intolerance in transgenic mice. Insulin secretion was reduced (0.5 vs. 0.1 ng/ml; P < 0.05), and critical ß-cell transcription factors Pdx1 and Nkx6.1 were significantly decreased. Impaired DISC1 allowed inappropriate activation of GSK3ß in ß cells, and antagonizing GSK3ß (SB216763; IC50 = 34.3 nM) rescued the ß-cell defects. These results uncover an unexpected role for DISC1 in normal ß-cell physiology and suggest that DISC1 dysregulation contributes to T2D independently of its importance for cognition.

The influence of type 1 diabetes on pancreatic weight.

AIMS/HYPOTHESIS: Previous studies of pancreases obtained at autopsy or by radiography note reduced pancreas weight (PW) and size, respectively, in type 1 diabetes; this finding is widely considered to be the result of chronic insulinopenia. This literature is, however, limited with respect to the influence of age, sex, anthropometric factors and disease duration on these observations. Moreover, data are sparse for young children, a group of particular interest for type 1 diabetes. We hypothesised that the pancreas-to-body weight ratio would normalise confounding inter-subject factors, thereby permitting better characterisation of PW in type 1 diabetes. METHODS: Transplant-grade pancreases were recovered from 216 organ donors with type 1 diabetes (n = 90), type 2 diabetes (n = 40) and no diabetes (n = 86). Whole-organ and head, body and tail weights were determined. The relative PW (RPW; PW [g] / body weight [kg]) was calculated and tested for normalisation of potential differences due to age, sex and BMI. RESULTS: PW significantly correlated with body weight in control donors (R (2) = 0.76, p < 0.001) while RPW (1.03 ± 0.36, mean ± SD) did not significantly differ across ages (0-58 years). Donors with type 1 diabetes (0.57 ± 0.18, p < 0.001), but not those with type 2 diabetes (0.93 ± 0.30), had significantly lower RPW. The relative weights of each pancreatic region from donors with type 1 diabetes were significantly smaller than those of regions from control donors and donors with type 2 diabetes (p < 0.001). Perhaps most interestingly, the RPW was not significantly associated with duration of type 1 diabetes or type 2 diabetes. CONCLUSIONS/INTERPRETATION: RPW allows for comparisons across a wide range of donor ages by eliminating confounding variables. These data validate an interesting feature of the type 1 diabetes pancreas and underscore the need for additional studies to identify the mechanistic basis for this finding, including those beyond the chronic loss of endogenous insulin secretion.

Abnormalities of the Exocrine Pancreas in Type 1 Diabetes.

Type 1 diabetes (T1D) is considered a pancreatic beta cell-specific disease that results in absolute insulin deficiency. Nevertheless, clinical studies from 1940 onwards showed that patients with T1D had an abnormal exocrine pancreas due to the presence of subclinical exocrine insufficiency and acinar atrophy. Exocrine abnormalities are an important, and mostly neglected, characteristic associated with T1D. It is however still unclear whether the exocrine dysfunction in T1D is a primary damage caused by the same pathogenic event that led to beta cell destruction or secondary to beta cell loss. In this review, we collect evidence supporting the hypothesis that T1D is a combined endocrine-exocrine disease in which the loss of functional beta cell mass is most clinically apparent.

Organ donor specimens: What can they tell us about type 1 diabetes?

Type 1 diabetes (T1D) is a chronic disease resulting from the destruction of pancreatic beta cells, due to a poorly understood combination of genetic, environmental, and immune factors. The JDRF Network for Pancreatic Organ donors with Diabetes (nPOD) program recovers transplantation quality pancreas from organ donors throughout the USA. In addition to recovery of donors with T1D, non-diabetic donors include those with islet autoantibodies. Donors with type 2 diabetes and other conditions are also recovered to aid investigations directed at the full spectrum of pathophysiological mechanisms affecting beta cells. One central processing laboratory conducts standardized procedures for sample processing, storage, and distribution, intended for current and future cutting edge investigations. Baseline histology characterizations are performed on the pancreatic samples, with images of the staining results provided though whole-slide digital scans. Uniquely, these high-grade biospecimens are provided without expense to investigators, working worldwide, seeking methods for disease prevention and reversal strategies. Collaborative working groups are highly encouraged, bringing together multiple investigators with different expertise to foster collaborations in several areas of critical need. This mini-review will provide some key histopathological findings emanating from the nPOD collection, including the heterogeneity of beta cell loss and islet inflammation (insulitis), beta cell mass, insulin-producing beta cells in chronic T1D, and pancreas weight reductions at disease onset. Analysis of variations in histopathology observed from these organ donors could provide for mechanistic differences related to etiological agents and serve an important function in terms of identifying the heterogeneity of T1D.

New insight on human type 1 diabetes biology: nPOD and nPOD-transplantation.

The Juvenile Diabetes Research Foundation (JDRF) Network for Pancreatic Organ Donors with Diabetes (JDRF nPOD) was established to obtain human pancreata and other tissues from organ donors with type 1 diabetes (T1D) in support of research focused on disease pathogenesis. Since 2007, nPOD has recovered tissues from over 100 T1D donors and distributed specimens to approximately 130 projects led by investigators worldwide. More recently, nPOD established a programmatic expansion that further links the transplantation world to nPOD, nPOD-Transplantation; this effort is pioneering novel approaches to extend the study of islet autoimmunity to the transplanted pancreas and to consent patients for postmortem organ donation directed towards diabetes research. Finally, nPOD actively fosters and coordinates collaborative research among nPOD investigators, with the formation of working groups and the application of team science approaches. Exciting findings are emerging from the collective work of nPOD investigators, which covers multiple aspects of islet autoimmunity and beta cell biology.

The Juvenile Diabetes Research Foundation Network for Pancreatic Organ Donors with Diabetes (nPOD) Program: goals, operational model and emerging findings.

nPOD actively promotes a multidisciplinary and unbiased approach toward a better understanding of T1D and identify novel therapeutic targets, through its focus on the study of human samples. Unique to this effort is the coordination of collaborative efforts and real-time data sharing. Studies supported by nPOD are providing direct evidence that human T1D isa complex and heterogeneous disease, in which a multitude of pathogenic factors may be operational and may contribute to the onset of the disease. Importantly, the concept that beta cell destruction is almost completed and that the autoimmune process is almost extinguished soon after diagnosis is being challenged. nPOD investigators are exploring the hypothesis that beta cell dysfunction may also be a significant cause of hyperglycemia, at least around the time of diagnosis, and are uncovering novel molecules and pathways that are linked to the pathogenesis and etiology of human T1D. The validation of therapeutic targets is also a key component of this effort, with recent and future findings providing new strategic direction for clinical trials.

Type 1 diabetes prevention clinical trial simulator: Case reports of model-informed drug development tool.

Clinical trials seeking to delay or prevent the onset of type 1 diabetes (T1D) face a series of pragmatic challenges. Despite more than 100 years since the discovery of insulin, teplizumab remains the only FDA-approved therapy to delay progression from Stage 2 to Stage 3 T1D. To increase the efficiency of clinical trials seeking this goal, our project sought to inform T1D clinical trial designs by developing a disease progression model-based clinical trial simulation tool. Using individual-level data collected from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies, we previously developed a quantitative joint model to predict the time to T1D onset. We then applied trial-specific inclusion/exclusion criteria, sample sizes in treatment and placebo arms, trial duration, assessment interval, and dropout rate. We implemented a function for presumed drug effects. To increase the size of the population pool, we generated virtual populations using multivariate normal distribution and ctree machine learning algorithms. As an output, power was calculated, which summarizes the probability of success, showing a statistically significant difference in the time distribution until the T1D diagnosis between the two arms. Using this tool, power curves can also be generated through iterations. The web-based tool is publicly available: https://app.cop.ufl.edu/t1d/. Herein, we briefly describe the tool and provide instructions for simulating a planned clinical trial with two case studies. This tool will allow for improved clinical trial designs and accelerate efforts seeking to prevent or delay the onset of T1D.

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in both normal and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the largest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in terms of identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables to identify protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Association of computed tomography scan-assessed body composition with immune and PI3K/AKT pathway proteins in distinct breast cancer tumor components.

This hypothesis-generating study aims to examine the extent to which computed tomography-assessed body composition phenotypes are associated with immune and PI3K/AKT signaling pathways in breast tumors. A total of 52 patients with newly diagnosed breast cancer were classified into four body composition types: adequate (lowest two tertiles of total adipose tissue [TAT]) and highest two tertiles of total skeletal muscle [TSM] areas); high adiposity (highest tertile of TAT and highest two tertiles of TSM); low muscle (lowest tertile of TSM and lowest two tertiles of TAT); and high adiposity with low muscle (highest tertile of TAT and lowest tertile of TSM). Immune and PI3K/AKT pathway proteins were profiled in tumor epithelium and the leukocyte-enriched stromal microenvironment using GeoMx (NanoString). Linear mixed models were used to compare log2-transformed protein levels. Compared with the normal type, the low muscle type was associated with higher expression of INPP4B (log2-fold change = 1.14, p = 0.0003, false discovery rate = 0.028). Other significant associations included low muscle type with increased CTLA4 and decreased pan-AKT expression in tumor epithelium, and high adiposity with increased CD3, CD8, CD20, and CD45RO expression in stroma (P<0.05; false discovery rate >0.2). With confirmation, body composition can be associated with signaling pathways in distinct components of breast tumors, highlighting the potential utility of body composition in informing tumor biology and therapy efficacies.

DNA Methylation-Based Assessment of Cell Composition in Human Pancreas and Islets.

Assessment of pancreas cell type composition is crucial to the understanding of the genesis of diabetes. Current approaches use immunodetection of protein markers, for example, insulin as a marker of ß-cells. A major limitation of these methods is that protein content varies in physiological and pathological conditions, complicating the extrapolation to actual cell number. Here, we demonstrate the use of cell type-specific DNA methylation markers for determining the fraction of specific cell types in human islet and pancreas specimens. We identified genomic loci that are uniquely demethylated in specific pancreatic cell types and applied targeted PCR to assess the methylation status of these loci in tissue samples, enabling inference of cell type composition. In islet preparations, normalization of insulin secretion to ß-cell DNA revealed similar ß-cell function in pre-type 1 diabetes (T1D), T1D, and type 2 diabetes (T2D), which was significantly lower than in donors without diabetes. In histological pancreas specimens from recent-onset T1D, this assay showed ß-cell fraction within the normal range, suggesting a significant contribution of ß-cell dysfunction. In T2D pancreata, we observed increased α-cell fraction and normal ß-cell fraction. Methylation-based analysis provides an accurate molecular alternative to immune detection of cell types in the human pancreas, with utility in the interpretation of insulin secretion assays and the assessment of pancreas cell composition in health and disease.

Empowerment Through Feminist Self-Defense: The IMPACT Lasts.

What do women learn in feminist self-defense that is empowering? This study examined the skills women used months and years after completing an IMPACT self-defense course. Ninety-seven survey participants described skills they had used and incorporated into their lives. The major themes that emerged through a classic grounded theory analysis were awareness, boundary setting, assertive body language, and managing adrenaline to prevent, interrupt, or stop uncomfortable, intrusive, or hostile behaviors. IMPACT-trained women did not engage in self-blaming or risky behavior and used their skills to prevent and interrupt aggressive behavior.

Transcriptional Profile of Human Pancreatic Acinar Ductal Metaplasia.

BACKGROUND AND AIMS: Aberrant acinar to ductal metaplasia (ADM), one of the earliest events involved in exocrine pancreatic cancer development, is typically studied using pancreata from genetically engineered mouse models. METHODS: We used primary, human pancreatic acinar cells from organ donors to evaluate the transcriptional and pathway profiles during the course of ADM. RESULTS: Following 6 days of three-dimensional culture on Matrigel, acinar cells underwent morphological and molecular changes indicative of ADM. mRNA from 14 donors' paired cells (day 0, acinar phenotype and day 6, ductal phenotype) was subjected to whole transcriptome sequencing. Acinar cell specific genes were significantly downregulated in the samples from the day 6 cultures while ductal cell-specific genes were upregulated. Several regulons of ADM were identified including transcription factors with reduced activity (PTF1A, RBPJL, and BHLHA15) and those ductal and progenitor transcription factors with increased activity (HNF1B, SOX11, and SOX4). Cells with the ductal phenotype contained higher expression of genes increased in pancreatic cancer while cells with an acinar phenotype had lower expression of cancer-associated genes. CONCLUSION: Our findings support the relevancy of human in vitro models to study pancreas cancer pathogenesis and exocrine cell plasticity.

Disease progression joint model predicts time to type 1 diabetes onset: Optimizing future type 1 diabetes prevention studies.

Clinical trials seeking type 1 diabetes prevention are challenging in terms of identifying patient populations likely to progress to type 1 diabetes within limited (i.e., short-term) trial durations. Hence, we sought to improve such efforts by developing a quantitative disease progression model for type 1 diabetes. Individual-level data obtained from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies were used to develop a joint model that links the longitudinal glycemic measure to the timing of type 1 diabetes diagnosis. Baseline covariates were assessed using a stepwise covariate modeling approach. Our study focused on individuals at risk of developing type 1 diabetes with the presence of two or more diabetes-related autoantibodies (AAbs). The developed model successfully quantified how patient features measured at baseline, including HbA1c and the presence of different AAbs, alter the timing of type 1 diabetes diagnosis with reasonable accuracy and precision (<30% RSE). In addition, selected covariates were statistically significant (p < 0.0001 Wald test). The Weibull model best captured the timing to type 1 diabetes diagnosis. The 2-h oral glucose tolerance values assessed at each visit were included as a time-varying biomarker, which was best quantified using the sigmoid maximum effect function. This model provides a framework to quantitatively predict and simulate the time to type 1 diabetes diagnosis in individuals at risk of developing the disease and thus, aligns with the needs of pharmaceutical companies and scientists seeking to advance therapies aimed at interdicting the disease process.