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Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories.

ABSTRACT: Development of islet autoimmunity precedes the onset of type 1 diabetes in children, however, the presence of autoantibodies does not necessarily lead to manifest disease and the onset of clinical symptoms is hard to predict. Here we show, by longitudinal sampling of islet autoantibodies (IAb) to insulin, glutamic acid decarboxylase and islet antigen-2 that disease progression follows distinct trajectories. Of the combined Type 1 Data Intelligence cohort of 24662 participants, 2172 individuals fulfill the criteria of two or more follow-up visits and IAb positivity at least once, with 652 progressing to type 1 diabetes during the 15 years course of the study. Our Continuous-Time Hidden Markov Models, that are developed to discover and visualize latent states based on the collected data and clinical characteristics of the patients, show that the health state of participants progresses from 11 distinct latent states as per three trajectories (TR1, TR2 and TR3), with associated 5-year cumulative diabetes-free survival of 40% (95% confidence interval [CI], 35% to 47%), 62% (95% CI, 57% to 67%), and 88% (95% CI, 85% to 91%), respectively (p < 0.0001). Age, sex, and HLA-DR status further refine the progression rates within trajectories, enabling clinically useful prediction of disease onset.

SUBMITTER: Kwon BC

PROVIDER: S-EPMC8938551 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories.

Kwon Bum Chul BC Anand Vibha V Achenbach Peter P Dunne Jessica L JL Hagopian William W Hu Jianying J Koski Eileen E Lernmark Åke Å Lundgren Markus M Ng Kenney K Toppari Jorma J Veijola Riitta R Frohnert Brigitte I BI

Nature communications 20220321 1

Development of islet autoimmunity precedes the onset of type 1 diabetes in children, however, the presence of autoantibodies does not necessarily lead to manifest disease and the onset of clinical symptoms is hard to predict. Here we show, by longitudinal sampling of islet autoantibodies (IAb) to insulin, glutamic acid decarboxylase and islet antigen-2 that disease progression follows distinct trajectories. Of the combined Type 1 Data Intelligence cohort of 24662 participants, 2172 individuals f ...[more]

PMID: 35314671

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Project description:BackgroundAlthough various therapies have been developed to treat malalignment in osteoarthritic knees, the pattern of malalignment progression is still unclear. This study aimed to identify homogeneous subgroups with distinct trajectories of malalignment progression in subjects with symptomatic knee osteoarthritis (KOA) and to determine corresponding risk factors.MethodsEight-year follow-up (from 2004 to 2012) data on 1252 participants with symptomatic KOA from the Osteoarthritis Initiative were included. Varus/valgus angle progression was characterized by group-based trajectory models. Time-varying covariates were introduced into the model to investigate how they affected trajectories. Multinomial logistic regression for trajectory group membership was applied to ascertain risk factors.ResultsFive subgroups were identified. Participants in the varus worsening trajectory (n = 166) or valgus worsening trajectory (n = 118) proceeded to worsen malalignment over time. The neutral trajectory (n = 378), varus stable trajectory (n = 328), and valgus stable trajectory (n = 262) maintained close to the initial varus/valgus angle over 8 years. Higher baseline Kellgren and Lawrence grade (odds ratio [OR] = 4.35, P < 0.001 for varus; OR = 3.85, P < 0.001 for valgus) and "severe" baseline malalignment (OR = 13.57, P < 0.001 for varus; OR = 23.04, P < 0.001 for valgus) were risk factors for worsening trajectories. The cutoff point of the baseline varus/valgus angle to discriminate between stable or worsening trajectory was -4.5° for varus and 3.6° for valgus.ConclusionsThis study identified the malalignment progression pattern - minor malalignment (-4.5° to +3.6°) tends to remain stable, while major baseline malalignment is likely to progress. This provides a reference for therapy to prevent malalignment from deteriorating and emphasizes the necessity of determining the trigger factors for malalignment onset.

Project description:Type 1 diabetes (T1D) and autoimmune thyroid disease (AITD) are the most frequent chronic autoimmune diseases worldwide. Several autoimmune endocrine and non-endocrine disorders tend to occur together. T1D and AITD often cluster in individuals and families, seen in the formation of autoimmune polyendocrinopathy (AP). The close relationship between these two diseases is largely explained by sharing a common genetic background. The HLA antigens DQ2 (DQA1*0501-DQB1*0201) and DQ8 (DQA1*0301-DQB1*0302), tightly linked with DR3 and DR4, are the major common genetic predisposition. Moreover, functional single nucleotide polymorphisms (or rare variants) of various genes, such as the cytotoxic T-lymphocyte- associated antigen (CTLA4), the protein tyrosine phosphatase non-receptor type 22 (PTPN22), the interleukin-2 Receptor (IL2Ra), the Vitamin D receptor (VDR), and the tumor-necrosis-factor-α (TNF) that are involved in immune regulation have been identified to confer susceptibility to both T1D and AITD. Other genes including cluster of differentiation 40 (CD40), the forkhead box P3 (FOXP3), the MHC Class I Polypeptide-Related Sequence A (MICA), insulin variable number of tandem repeats (INS-VNTR), the C-Type Lectin Domain Containing 16A (CLEC16A), the Erb-B2 Receptor Tyrosine Kinase 3 (ERBB3) gene, the interferon-induced helicase C domain-containing protein 1 (IFIH1), and various cytokine genes are also under suspicion to increase susceptibility to T1D and AITD. Further, BTB domain and CNC homolog 2 (BACH2), C-C motif chemokine receptor 5 (CCR5), SH2B adaptor protein 3 (SH2B3), and Rac family small GTPase 2 (RAC2) are found to be associated with T1D and AITD by various independent genome wide association studies and overlap in our list, indicating a strong common genetic link for T1D and AITD. As several susceptibility genes and environmental factors contribute to the disease aetiology of both T1D and AITD and/or AP subtype III variant (T1D+AITD) simultaneously, all patients with T1D should be screened for AITD, and vice versa.

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Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories.

Publications

Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories.

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