B lymphocyte alterations accompany abatacept resistance in new-onset type 1 diabetes.

Costimulatory interactions control T cell activation at sites of activated antigen-presenting cells, including B cells. Blockade of the CD28/CD80/CD86 costimulatory axis with CTLA4Ig (abatacept) is widely used to treat certain autoimmune diseases. While transiently effective in subjects with new-onset type 1 diabetes (T1D), abatacept did not induce long-lasting immune tolerance. To elucidate mechanisms limiting immune tolerance in T1D, we performed unbiased analysis of whole blood transcriptomes and targeted measurements of cell subset levels in subjects from a clinical trial of abatacept in new-onset T1D. We showed that individual subjects displayed age-related immune phenotypes ("immunotypes") at baseline, characterized by elevated levels of B cells or neutrophils, that accompanied rapid or slow progression, respectively, in both abatacept- and placebo-treated groups. A more pronounced immunotype was exhibited by a subset of subjects showing poor response (resistance) to abatacept. This resistance immunotype was characterized by a transient increase in activated B cells (one of the cell types that binds abatacept), reprogrammed costimulatory ligand gene expression, and reduced inhibition of anti-insulin antibodies. Our findings identify immunotypes in T1D subjects that are linked to the rate of disease progression, both in placebo- and abatacept-treated subjects. Furthermore, our results suggest therapeutic approaches to restore immune tolerance in T1D.

[1]  P. Linsley,et al.  Cell type-specific immune phenotypes predict loss of insulin secretion in new-onset type 1 diabetes. , 2019, JCI insight.

[2]  P. Linsley,et al.  Abnormal neutrophil signature in the blood and pancreas of presymptomatic and symptomatic type 1 diabetes. , 2018, JCI insight.

[3]  M. Hessner,et al.  Innate immune activity as a predictor of persistent insulin secretion and association with responsiveness to CTLA4-Ig treatment in recent-onset type 1 diabetes , 2018, Diabetologia.

[4]  Scott R. Presnell,et al.  Elevated T cell levels in peripheral blood predict poor clinical response following rituximab treatment in new-onset type 1 diabetes , 2018, Genes & Immunity.

[5]  J. Krischer,et al.  Strength in Numbers: Opportunities for Enhancing the Development of Effective Treatments for Type 1 Diabetes—The TrialNet Experience , 2018, Diabetes.

[6]  P. Bingley,et al.  Type 1 Diabetes TrialNet: A Multifaceted Approach to Bringing Disease-Modifying Therapy to Clinical Use in Type 1 Diabetes , 2018, Diabetes Care.

[7]  Mark M. Davis,et al.  Continuous immunotypes describe human immune variation and predict diverse responses , 2017, Proceedings of the National Academy of Sciences.

[8]  G. Schett,et al.  Effects of DMARDs on citrullinated peptide autoantibody levels in RA patients-A longitudinal analysis. , 2017, Seminars in arthritis and rheumatism.

[9]  H. Kolb,et al.  Immunotherapy for Type 1 Diabetes: Why Do Current Protocols Not Halt the Underlying Disease Process? , 2017, Cell metabolism.

[10]  James A. Eddy,et al.  Partial exhaustion of CD8 T cells and clinical response to teplizumab in new-onset type 1 diabetes , 2016, Science Immunology.

[11]  Damian Szklarczyk,et al.  The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible , 2016, Nucleic Acids Res..

[12]  N. Morgan,et al.  Differential Insulitic Profiles Determine the Extent of β-Cell Destruction and the Age at Onset of Type 1 Diabetes , 2016, Diabetes.

[13]  Andres Metspalu,et al.  The transcriptional landscape of age in human peripheral blood , 2015, Nature Communications.

[14]  Rui-Ru Ji,et al.  Abatacept Inhibition of T Cell Priming in Mice by Induction of a Unique Transcriptional Profile That Reduces Their Ability to Activate Antigen‐Presenting Cells , 2015, Arthritis & rheumatology.

[15]  L. Dimeglio,et al.  Defining Pathways for Development of Disease-Modifying Therapies in Children With Type 1 Diabetes: A Consensus Report , 2015, Diabetes Care.

[16]  W. Robinson,et al.  Impact of baseline anti-cyclic citrullinated peptide-2 antibody concentration on efficacy outcomes following treatment with subcutaneous abatacept or adalimumab: 2-year results from the AMPLE trial , 2015, Annals of the rheumatic diseases.

[17]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[18]  Peter S. Linsley,et al.  Copy Number Loss of the Interferon Gene Cluster in Melanomas Is Linked to Reduced T Cell Infiltrate and Poor Patient Prognosis , 2014, PloS one.

[19]  P. Bingley,et al.  Blood and Islet Phenotypes Indicate Immunological Heterogeneity in Type 1 Diabetes , 2014, Diabetes.

[20]  Kenneth G. C. Smith,et al.  CD28 expression is required after T cell priming for helper T cell responses and protective immunity to infection , 2014, eLife.

[21]  L. Spain,et al.  Reduction in CD4 Central Memory T-Cell Subset in Costimulation Modulator Abatacept-Treated Patients With Recent-Onset Type 1 Diabetes Is Associated With Slower C-Peptide Decline , 2014, Diabetes.

[22]  M. Rigby,et al.  Targeted immune interventions for type 1 diabetes: not as easy as it looks! , 2014, Current opinion in endocrinology, diabetes, and obesity.

[23]  Darrell M. Wilson,et al.  Costimulation Modulation With Abatacept in Patients With Recent-Onset Type 1 Diabetes: Follow-up 1 Year After Cessation of Treatment , 2014, Diabetes Care.

[24]  Charity W. Law,et al.  voom: precision weights unlock linear model analysis tools for RNA-seq read counts , 2014, Genome Biology.

[25]  M. Chiarini,et al.  Reduction of peripheral blood T cells producing IFN-γ and IL-17 after therapy with abatacept for rheumatoid arthritis. , 2014, Clinical and experimental rheumatology.

[26]  Darrell M. Wilson,et al.  B-Lymphocyte Depletion With Rituximab and β-Cell Function: Two-Year Results , 2014, Diabetes Care.

[27]  W. Hagopian,et al.  Teplizumab (Anti-CD3 mAb) Treatment Preserves C-Peptide Responses in Patients With New-Onset Type 1 Diabetes in a Randomized Controlled Trial , 2013, Diabetes.

[28]  L. Walker Treg and CTLA-4: Two intertwining pathways to immune tolerance , 2013, Journal of autoimmunity.

[29]  P. Marchetti,et al.  Reduction of Circulating Neutrophils Precedes and Accompanies Type 1 Diabetes , 2013, Diabetes.

[30]  M. Peakman,et al.  Progress in immune‐based therapies for type 1 diabetes , 2013, Clinical and experimental immunology.

[31]  Lieping Chen,et al.  Molecular mechanisms of T cell co-stimulation and co-inhibition , 2013, Nature Reviews Immunology.

[32]  Y. Simoni,et al.  Crosstalk between neutrophils, B-1a cells and plasmacytoid dendritic cells initiates autoimmune diabetes , 2012, Nature Medicine.

[33]  C. Beam,et al.  Fall in C-Peptide During First 2 Years From Diagnosis , 2012, Diabetes.

[34]  D. Schatz,et al.  Through the Fog: Recent Clinical Trials to Preserve β-Cell Function in Type 1 Diabetes , 2012, Diabetes.

[35]  H. Ochs,et al.  Effect of rituximab on human in vivo antibody immune responses. , 2011, The Journal of allergy and clinical immunology.

[36]  J. Krischer,et al.  Rituximab Selectively Suppresses Specific Islet Antibodies , 2011, Diabetes.

[37]  Darrell M. Wilson,et al.  Co-stimulation modulation with abatacept in patients with recent-onset type 1 diabetes: a randomised, double-blind, placebo-controlled trial , 2011, The Lancet.

[38]  R. González-Amaro,et al.  CTLA-4-Ig Therapy Diminishes the Frequency but Enhances the Function of Treg Cells in Patients with Rheumatoid Arthritis , 2011, Journal of Clinical Immunology.

[39]  P. Linsley,et al.  Pillars article: long-term acceptance of skin and cardiac allografts after blocking CD40 and CD28 pathways. Nature. 1996. 381: 434-438. 1996. , 2011, Journal of immunology.

[40]  I. McInnes,et al.  Abatacept Limits Breach of Self-Tolerance in a Murine Model of Arthritis via Effects on the Generation of T Follicular Helper Cells , 2010, The Journal of Immunology.

[41]  Darrell M. Wilson,et al.  Rituximab, B-lymphocyte depletion, and preservation of beta-cell function. , 2009, The New England journal of medicine.

[42]  Davis J. McCarthy,et al.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..

[43]  E. Renard,et al.  Circulating insulin antibodies: influence of continuous subcutaneous or intraperitoneal insulin infusion, and impact on glucose control , 2009, Diabetes/metabolism research and reviews.

[44]  P. Linsley,et al.  The clinical utility of inhibiting CD28‐mediated costimulation , 2009, Immunological reviews.

[45]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[46]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[47]  P. Linsley,et al.  Immunosuppression in vivo by a soluble form of the CTLA-4 T cell activation molecule. , 1992, Science.

[48]  P. Linsley,et al.  CTLA-4 is a second receptor for the B cell activation antigen B7 , 1991, The Journal of experimental medicine.

[49]  Y. Benjamini,et al.  More powerful procedures for multiple significance testing. , 1990, Statistics in medicine.

[50]  A. Ziegler,et al.  Concentration of Insulin Autoantibodies at Onset of Type I Diabetes: Inverse Log-Linear Correlation With Age , 1988, Diabetes Care.

[51]  M. Robinson,et al.  A scaling normalization method for differential expression analysis of RNA-seq data , 2010, Genome Biology.

[52]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .