Study design and setting
This study was designed to compare the phenotypes of circulating B and T cells (using flow cytometry to analyse cell-surface markers) and levels of serum chemokines and cytokines in healthy donors and people with newly diagnosed or long-standing type 1 diabetes. Venous blood samples were collected from individuals in South Wales between 2012 and 2014. Peripheral blood mononuclear cells (PBMCs) were analysed in two batches (2013 and 2014). Serum samples were cryopreserved and analysed as a single batch.
Participants
Adults with newly diagnosed or long-standing type 1 diabetes were recruited for this study, together with age- and sex-matched healthy donors (age was matched to ±2 years). Type 1 diabetes was diagnosed according to criteria established by the American Diabetes Association [10]. Insulin treatment was commenced within 1 month of diagnosis. Time from diagnosis was categorised as less than 1 year for newly diagnosed individuals and more than 3 years for those with long-standing diabetes. Age- and sex-matched healthy donors were seronegative for islet-specific autoantibodies, with no personal or family history of type 1 diabetes or other autoimmune conditions. The discovery cohort (Study A) included n = 10 newly diagnosed individuals (mean age 33.4 years, range 23–44 years), n = 10 individuals with long-standing diabetes (mean age 40.2 years, range 29–50 years) and n = 15 healthy donors (mean age 38.2 years, range 24–50 years). The validation cohort (Study B) included n = 10 newly diagnosed individuals (mean age 24.3 years, range 19–34 years), n = 10 individuals with long-standing diabetes (mean age 38.5 years, range 23–48 years) and n = 14 healthy donors (mean age 32.5 years, range 22–48 years). Additional participants were recruited for immunoassay analysis of serum chemokines and cytokines (n = 34 newly diagnosed individuals; n = 21 individuals with long-standing diabetes; n = 33 healthy donors, not matched). Cohort details are summarised in electronic supplementary material (ESM) Tables 1–3.
Ethics
This study was approved by the South East Wales Research Ethics Committee and conducted in accordance with the principles of Good Clinical Practice established by the International Council for Harmonisation and the World Health Organization. All participants provided written informed consent prior to enrolment, as mandated by the Declaration of Helsinki.
Islet-specific autoantibodies
Serum autoantibodies specific for GAD, islet antigen-2 and zinc transporter-8 were quantified by ELISA (RSR, Cardiff, UK). Positive thresholds were set at 5 U/ml for GAD, 7.5 U/ml for islet antigen-2 and 15 U/ml for zinc transporter-8.
HLA class II genotyping
Genomic DNA was extracted from whole blood samples collected in EDTA. HLA-DRB alleles (DRB1*0101-0103, DRB1*1501-1505, DRB1*1601-1606, DRB1*0301, DRB1*0401-0422, DRB1*1101-1121, DRB1*1201-1203, DRB1*1302-1305/DRB1*1303-1304, DRB1*1401/1404/1405, DRB1*0701-0702, DRB1*0805-0801, DRB1*0901, DRB1*1001, DRB3*0101-0301 and DRB4*0101) were resolved using PCRs with sequence-specific primers [11] (ESM Table 4).
Blood samples
PBMCs were isolated from heparinised samples of whole blood via density gradient centrifugation using Lymphoprep (STEMCELL Technologies, Cambridge, UK). Aliquots of 5–20 × 106 PBMCs/ml per vial were stored in liquid nitrogen after cooling overnight to −80°C at a controlled rate of −1°C/min in 90% AIM-V medium (Thermo Fisher Scientific, Hemel Hempstead, UK) supplemented with 10% dimethyl sulfoxide (Sigma-Aldrich, Gillingham, UK) (vol./vol.).
Flow cytometry
Thawed PBMCs were blocked using TruStain (BioLegend, San Diego, CA, USA) for 5 min at room temperature, stained with LIVE/DEAD Fixable Aqua (Thermo Fisher Scientific) for 10 min at room temperature and labelled with titrated concentrations of the following monoclonal antibodies for 30 min at 4°C: α-CD19-PE-Cy7 (clone SJ25C1) and α-CD24-APC-eFluor780 (clone SN3) (both from eBioscience, San Diego, CA, USA); α-CD3-BV711 (clone OKT3), α-CD45R/B220-BV421 (clone RA3-6B2) and α-IgD-AF488 (clone IA6-2) (all from BioLegend); α-CD27-Q605 (clone CLB-27/1) (Thermo Fisher Scientific); α-CD21-PE-Cy5 (clone B-ly4), α-CD38-PE-CF594 (clone HIT2) and α-C-X-C motif chemokine receptor 3 (CXCR3)-PE (clone IC6/CXCR3) (all from BD Biosciences, Franklin Lakes, NJ, USA); and α-CD95-APC (clone DX2) (Miltenyi Biotec, Bergisch Gladbach, Germany). Cells were then washed in PBS containing 0.5% BSA (wt/vol.) and 2 mmol/l EDTA, fixed with 1% paraformaldehyde (wt/vol.) and acquired using a special-order system FACSAria II flow cytometer (BD Biosciences). Further details are available in ESM Table 5. Data were acquired in a blinded fashion and analysed using FlowJo software version 10 (Tree Star, Ashland, OR, USA).
Spanning-tree progression analysis of density-normalised events
Live B cells were identified in serial gates as singlets, lymphocytes, LIVE/DEAD Fixable Aqua−, CD3− and CD19+ events using FlowJo software version 10. Compensated flow cytometry standard files were exported and concatenated for spanning-tree progression analysis of density-normalised events (SPADE) using fixed settings (K-means algorithm, 100 clusters and arcsinh transformation with cofactor 150) in SPADE software version 3.0 (http://pengqiu.gatech.edu/software/SPADE/) [12, 13]. The following markers were included in the analysis: CD19, CD21, CD24, CD27, CD38, CD95, B220, CXCR3 and IgD. Auto-partitioning was used to divide the resulting trees into eight areas. Median expression of each marker was calculated for each donor in each node. Data from the two cohorts were tested for normality and then analysed separately because of differences in flow cytometer set-up between Study A and Study B. As the data were normally distributed, an unpaired Student’s t test was used to compare the transformed median fluorescence intensity (MFI) of each marker in each area for newly diagnosed individuals and those with long-standing diabetes vs healthy donors in Study A. The analysis was repeated in Study B for markers identified as significantly different in newly diagnosed individuals and those with long-standing diabetes relative to healthy donors in Study A. In a final step, B cells were gated manually, using FlowJo software version 10, to confirm differences in MFI for each marker of interest, and significance was assessed using a one-way ANOVA with Dunnett’s post hoc test.
Serum chemokines/cytokines
Serum samples were analysed using the U-PLEX platform (Meso Scale Diagnostics, Rockville, MD, USA) to quantify chemokine (C-X-C motif) ligand (CXCL)10, CXCL11, IL-4, IL-6, IL-10 and IFN-γ or using DuoSet ELISA kits to quantify CXCL9, B cell activating factor (BAFF) and TGF-β (R&D Systems, Abingdon, UK). Data were analysed using the Kruskal–Wallis test with Dunn’s post hoc test.
Statistics
As there were no existing data to guide power calculations, and given the large number of variables under consideration, together with the modes of analysis we planned to employ simultaneously across all groups of participants, sample sizes were determined in part by feasibility. Significant results from Study A were treated as hypothesis-generating and tested for validation purposes in Study B. An unpaired Student’s t test was used to assess differences in mean values between two groups.
One-way ANOVA (for normally distributed data) or the Kruskal–Wallis test (for non-normally distributed data) were used with corrections for multiple comparisons to assess differences in mean values between three or more groups. All statistical tests were performed using Prism software version 6 (GraphPad, San Diego, CA, USA).