ORIGINAL ARTICLES Partial remission and early stages of pediatric type 1 diabetes display immunoregulatory changes. A pilot study ADRIAN VILLALBA, MIREIA FONOLLEDA, MARTA MURILLO, SILVIA RODRIGUEZ-FERNANDEZ, ROSA-MARIA AMPUDIA, DAVID PERNA-BARRULL, MARIA BELEN RAINA, BIBIANA QUIRANT-SANCHEZ, RAQUEL PLANAS, AINA TENIENTE-SERRA, JOAN BEL, and MARTA VIVES-PI BADALONA, AND BARCELONA, SPAIN Type 1 diabetes (T1D) is a chronic metabolic disease of unknown etiology that results from b-cell destruction. The onset of the disease, which arises after a long asymptomatic period of autoimmune attack, may be followed by a relapsing and remitting progression, a phenomenon that is most evident during the partial remis- sion phase (PR). This stage lasts for a few months, shows minor requirements of exog- enous insulin and could be explained by a recovery of immunological tolerance. This study aims to identify new biomarkers at early stages of pediatric T1D that reflect immunoregulatory changes. To that end, pediatric patients with T1D (n = 52) and age-related control subjects (n = 30) were recruited. Immune response-related molecules and lymphocyte subsets were determined starting at T1D onset and until the second year of progression. Results showed that circulating TGF-b levels decreased during PR, and that betatrophin concentration was increased in all the considered stages without differing among studied checkpoints. Moreover, an increase of regulatory T, B and NK subsets was found during T1D progression, proba- bly reflecting an attempt to restore self-tolerance. By contrast, a reduction in mono- cyte levels was observed at the early stages of diabetes. The results reveal significant changes in immunological parameters during the different early stages of T1D in children, which could ultimately serve as potential biomarkers to charac- terize the progression of T1D. (Translational Research 2019; 210:825) Abbreviations: aTreg = activated regulatory T; BLMS = B lymphocyte maturation stages; BMI = body mass index; Breg = regulatory B; CM = central memory; DP = double-positive; From the Immunology Section, Germans Trias i Pujol Research Institute, Badalona, Spain; Pediatrics Section, Germans Trias i Pujol Research Insti- tute and University Hospital, Autonomous University of Barcelona, Badalona, Spain; CIBER of Diabetes and Associated Metabolic Disease (CIBERDEM). ISCIII, Barcelona, Spain. Submitted for Publication December 11, 2018; received submitted March 4, 2019; accepted for publication March 7, 2019. Reprint requests: Marta Vives-Pi, Immunology Section, Germans Trias i Pujol Research Institute. Carretera Canyet s/n., 08916 Badalona, Spain. E-mail address: mvives@igtp.cat. 1931-5244/$ - see front matter Ó 2019 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/ licenses/by-nc-nd/4.0/) https://doi.org/10.1016/j.trsl.2019.03.002 8 Translational Research Volume 210 Villalba et al 9 EM = effector memory; HbA1c = glycated hemoglobin; IDDAA1c = insulin dose-adjusted HbA1c; mTreg = memory regulatory T; NKreg = regulatory Natural Killer; PR = partial remission; PBMCs = peripheral blood mononuclear cells; Treg = regulatory T; TLMS = T lymphocyte matura- tion stages; T1D = type 1 diabetes specific, and highly reproducible detection method. At AT A GLANCE COMMENTARY present, most used biomarkers in T1D are metabolic Villalba A, et al. (HbA1c and C-peptide), but they do not reflect the pathophisiology of T1D. HbA1c is strongly dependent Background on daily glycemia and C-peptide levels are usually not This study provides new candidate biomarkers  detectable after the clinical onset.6 Autoantibodies betatrophin, TGF-b, and regulatory T, B and NK against b-cell antigens are immunological biomarkers subsets  that reflect the immunoregulatory for T1D but they do not always predict the develop- attempts during early progression of pediatric ment of the disease or the severity of secondary com- type 1 diabetes, including partial remission stage. plications. Specific autoreactive T cells were also proposed as biomarkers but the reproducibility of Translational Significance experiments involving antigen-specific T cells has These findings suggest that regulatory lympho- been questioned.7 cytes as well as betatrophin and TGF-b molecules Several candidate biomarker have arised in the last may be related to partial remission and progres- years. Betatrophin is one of these candidates, since sion of type 1 diabetes in children. Moreover, and its circulating levels in plasma were found increased because partial remission may be a good stage for in adult patients with long-standing T1D.8 Another immunointervention, these candidate biomarkers candidate was TGF-b, due to its role in immunoregu- can be considered for clinical trials. lation and the alterations found in the pancreases from patients.9 Moreover, plasma levels of TGF-b are increased in adult patients at the onset, indicating INTRODUCTION that TGF-b plays a role in chronic inflammation in T1D.10 Other candidates are molecules with altered Type 1 diabetes (T1D) is a metabolic disease expression in the pancreases from patients at differ- caused by the autoimmune destruction of insulin-pro- ent disease stages,11 and circulating leukocyte sub- ducing b-cells. After the clinical onset, and probably sets,12,13 that can be easily obtained from peripheral due to the beginning of insulin therapy, between 50% blood of pediatric subjects and be identified with a and 80% of pediatric patients with T1D undergo a high resolution in an automated manner.14 Our study partial remission (PR) phase, also known as honey- aims at unravelling for the first time the characteriza- moon, starting at 6 months of disease progression and tion of the changes in these markers/subsets during lasting up to 2 years.1 This transient period is defined the early stages of pediatric T1D. by low requirements of insulin and diminished gly- cated hemoglobin2,3 (HbA1c) and could be an optimal phase for immune intervention and other therapeutic strategies. Clinical trials using immunotherapies have MATERIAL AND METHODS failed to provide long-term b-cell protection, partly Participants. Pediatric patients with T1D (n = 52) due to the stage chosen for immunointervention.4 and age-related control subjects (n = 30) were included Hence, it is necessary to identify new biomarkers in this study (Table 1). All patients fulfilled the classifi- which will enable the monitoring of the PR and the cation criteria for T1D. Inclusion criteria were early stages of T1D. 118 years of age, and normal body mass index (BMI) A reliable biomarker has to be robust and allow for according to the Spanish BMI pediatric cohort growth the distinction of control and patients, or in this case, chart.15 Exclusion criteria were being under immuno- patients at different stages of disease. For T1D, it suppressive or anti-inflammatory treatment, the pres- should fulfil several requirements4: (1) To reflect the ence of other autoimmune diseases, type 2 diabetes, variations of the autoimmune response or b-cell regen- pregnancy, compromised kidney function, or liver dis- eration5; (2) To be easy to obtain with minimum dis- eases. All patients with T1D were positive for autoanti- comfort or risk for the patient; (3) To display bodies to GAD65 and/or IA-2 at the onset, and were variations over the progression of the disease; (4) To negative for other autoantibodies (antithyroglobulin, allow the monitoring of the patient’s response to anti-transglutaminase, and antithyroid peroxidase). immunotherapies; (5) To have available a sensitive, Twenty-two out of the total 52 patients and 14 out of 30 Translational Research 10 Villalba et al August 2019 Table 1. Clinical data for pediatric control subjects and patients with T1D at onset, and at 6, 12 and 18 months of disease progression Variable Control subjects Patients at Patients at 6 Patients at Patients at (n = 14) onset (n = 22) mo (n = 15) 12 mo (n = 14) 18 mo (n = 13) Age (years) 8.1 § 3.6 9.1 § 4.5 9.6 § 4.6 10.1 § 4.6 10.6 § 4.6 Gender (M/F) 3/11 11/11 8/7 8/6 9/5 BMI (kg/m2) 19.4 § 2.4 17.3 § 3.4 18.3 § 3.4 18.3 § 3.6 17.8 § 1.8 HbA1c (%) ND 11.4 § 2.5 7.2 § 1.1 7.7§ 1.04 7.6 § 1.04 HbA1c (mmol/mol) ND 101 § 27.3 55 § 11.6 61 § 11.4 61 § 11.4 Insulin dose (UI/kg/day) ND 0.8 § 0.4 0.53 § 0.2 0.79 § 0.7 0.92 § 0.72 IDDAA1C (%) ND 14.1 § 3.4 9.4 § 1.3 8.9 § 3.5 10.2 § 2.7 All values are mean § SD. No statistical differences were found in age between groups. Statistical differences were found in: insulin dose (onset vs 6 mo: <, 6 mo vs 12 mo: *, 6 mo vs 18 mo: x, 12 mo vs 18 mo: #); glycated hemoglobin (HbA1c) (onset vs 6 mo: x, onset vs 12 mo: #, onset vs 18 mo: #); insulin dose-adjusted HbA1c (IDDAA1c) (onset vs 6 mo: <, onset vs 12 mo: < and onset vs 18 mo: x). Statistics: Mann-Whitney test (*P < 0.05, # P < 0.01, x P < 0.001, < P < 0.0001). BMI, body mass index; HbA1c, glycated hemoglobin; IDDAA1c, insulin dose-adjusted HbA1c; ND, not determined. control subjects were selected to be included in the panel17: CD45 FITC, CD3 V450, CD4 PerCPCy5.5, ELISA experiments, whereas the remaining 30 patients CD25 PE, CCR4 PECy7, CD127 AF647, CD45RO and 16 control subjects were included in the leukocyte APCH7, HLA-DR V500; (3) T lymphocyte maturation subsets’ analysis. Patients were considered to be in PR stages panel16: CD3 V500, CD4 PerCPCy5.5, CD8 when they fulfilled one or both of the two accepted crite- APCH7, CD45RA FITC, PTK7 PE, CCR7 PECy7, ria. PR was defined as <0.5 UI/kg/d and <7% HbA1c, CD31 AF647, CD27 BV421; (4) Transitional B cell or <9 insulin dose-adjusted HbA1c3 (IDDAA1c). All panel16: CD19 PerCPCy5.5, CD24 FITC, CD38 PE, the participants gave informed consent, and the study CD27 APC; (5) B lymphocyte maturation stages was approved by the Committee on the Ethics of panel16: CD3 V450, CD19 V500, CD27 APC, CD21 Research of the Germans Trias i Pujol Research Institute PE, IgD FITC, IgM PerCPCy5.5; (6) gd T cell panel16: and Hospital. CD3 PerCP, gd TCR PE, ab TCR FITC, CD8 APCH7, ELISA. ELISA method was used to determine plas- CD4 V450 and (7) DC/Monocytes/NK17: CD45 matic concentrations of TGF-b (ThermoFisher Scien- AF700, CD3 APCH7, CD19 APCH7, CD14 V450, tific, Waltham, Massachusetts), betatrophin (Wuhan CD16 APC, CD11c PECy7, CD123 PerCPCy5.5, Eiaab Science, Wuhan, China), and HLA-G (sHLA-G, CD56 PE, HLA-DR V500, Slan FITC. At least 10,000 Enzo Life Sciences, Farmingdale, New York) in plasma leukocyte events per sample were acquired using samples obtained from control subjects and patients FACS Canto II and LSR Fortessa Flow Cytometers with T1D at the onset and at 6, 12, and 18 months of (BD Biosciences). Corresponding fluorescence minus progression of the disease. Basic analytical characteris- one staining was used as control. The gating strategy to tics of the methods were: for betatrophin, detection analyze specific leukocyte subsets was based on inter- range: 785000 pg/mL and sensitivity: >0.051 pg/mL; national consensus.18 Absolute counts (cells/mL) were for TGF-b, detection range: 81000 pg/mL and sensi- analyzed for all subsets using Perfect Count Micro- tivity: 8.6 pg/mL; for sHLA-G, detection range: spheres (Cytognos SL, Salamanca, Spain). Data were 3.91125 U/mL, and sensitivity: 0.6 U/mL. analyzed using FACSDiva software (BD Biosciences). Flow cytometry. For the analysis of cellular subsets, Quantitative RT-PCR. RNA was isolated using RNeasy fresh venous blood samples were collected in ethylene Micro Kit (QIAGEN) and reverse-transcribed with a diamine tetra acetic acid tubes from control subjects High Capacity cDNA Reverse Transcription Kit (Ther- and patients with T1D at the onset and at 6, 12, and 18 moFisher Scientific). cDNA synthesis was carried out months of disease progression. Samples of 1 mL of using random hexamers (0.5 mg/mL, BioTools, Valle whole blood were washed and erythrocytes were lysed de Tobalina, Madrid, Spain) and reverse transcriptase (Lysing Buffer, BD Biosciences, San Jose, California). Moloney murine Leukemia virus (200 U/mL, Promega, A sample of 100 mL was then marked with a panel of Madison, Wisconsin). Quantitative RT-PCR assays different monoclonal antibodies (BD Biosciences) at were performed on a LightCycler 480 (Roche Diagnos- room temperature and protected from light for 20 tics, Mannheim, Germany) using SYBR Green I Mas- minutes. The panels, detailed in Table 2, were built as ter mix (Roche Diagnostics) and specific primers for follows: (1) Th17 lymphocytes panel16: CD4 V450, HLA-E, HLA-F, TLR3, LYZ, CD36, IL-8, and CXCL1 CCR6 PE, CCR7 PECy7, and CCR4 AF647; (2) Treg (Invitrogen, Life Technologies, Gaithersburg, Translational Research Volume 210 Villalba et al 11 Table 2. Lymphocyte subsets analyzed in pediatric patients with T1D and their markers according to international consensus18 Lymphocyte subset Phenotype Reference subset aTreg CD3+CD4+CD127lowCD25+ CCR4+ CD45RO+HLADR+ mTreg mTreg CD3+CD4+CD127lowCD25+ CCR4+ CD45RO+ CD3+CD4+ Th17 CD4+ CCR7¡ CCR4+ CCR6+ CD4+ Breg CD19+CD27+CD24hi CD19+ NKreg CD3¡CD19¡CD56+CD14¡CD56brCD16¡ NK cells Monocytes CD3¡CD19¡CD14+ CD3¡CD19¡ CD14+CD16¡ CD3¡CD19¡CD14+CD16¡ Monocytes Total CD27+ CD19+CD27+ CD19+ Total B transitional CD19+CD27¡CD24hiCD38+ CD19+ B transitional high CD19+CD27¡CD24hiCD38hi CD19+ B transitional low CD19+CD27¡CD24hiCD38lo CD19+ ab CD3+ ab + ɣd ¡ CD3+ CD3+ DP CD3+CD4+CD8+ CD3+ ɣd CD8+ CD3+ ab ¡ ɣd +CD8+ Total ɣd CD3+CD4+ CD3+CD4+ Total lymphocytes Recent thymic emigrants CD3+CD4+CCR7+CD45RA+CD31+PTK7+ CD4+ Naive CD4+ CM CD3+CD4+CCR7+CD45RA¡CD27+ CD3+CD4+ CD4+ EM CD3+CD4+CCR7¡CD45RA¡ CD3+CD4+ CD4+ EM CD27+ CD3+CD4+CD27+CCR7¡CD45RA¡ CD3+CD4+ CD4+ EMRA CD3+CD4+CCR7¡CD45RA+ CD3+CD4+ CD4+ EMRA CD27+ CD3+CD4+CD27+CCR7¡CD45RA+ CD3+CD4+ CD4+ EMRA CD27¡ CD3+CD4+CD27¡CCR7¡CD45RA+ CD3+CD4+ CD3+CD8+ CD3+CD8+ Total lymphocytes CD8+Naive CD3+CD8+CCR7+CD45RA+CD27+ CD3+CD8+ CD8+ CM CD3+CD8+CCR7+CD45RA¡CD27+ CD3+CD8+ CD8+ EMRA CD3+CD8+CCR7¡CD45RA+ CD3+CD8+ CD8+ EMRA CD27+ CD3+CD8+CD27+CCR7¡CD45RA+ CD3+CD8+ aTreg, activated regulatory T cell; mTreg, memory regulatory T; Breg, regulatory B; NKreg, regulatory Natural Killer; DP, double positive; CM, central memory; EM, effector memory; EMRA, CD45+ effector memory. Maryland) (Supplementary Table 1). Relative quantifi- from these patients were obtained at 3 checkpoints: cation was performed by normalizing the expression of clinical onset (n = 14), 6 months (n = 13), and 12 each gene of interest to that of the housekeeping HPRT months (n = 13) of progression of the disease. TGF-b gene following the 2-DDCt method.19 concentration was significantly decreased at the check- Statistical analysis. The statistical analysis was per- point of first year when compared to the onset (Fig 1, formed using Prism 7.0. Software (GraphPad software A). Then, the possible correlation between this alter- Inc., San Diego, California). For comparisons of paired ation and PR was evaluated. In fact, there is a signifi- data, a nonparametric Wilcoxon test was used, whereas cant decrease in circulating levels of TGF-b in patients a nonparametric Mann-Whitney test was used for com- with PR at 6 and 12 months of disease progression (Fig parisons of unpaired data. To find statistically significant 1, B). In addition, patients at onset were divided in 2 correlations between parameters, Spearman’s test was groups (PR or not PR) and TGF-b levels were com- used. A P value of <0.05 was considered significant. pared to understand whether those with PR have a less aggressive T1D onset or rather have a real different evolution of their diabetes. The results showed that both groups have similar circulating TGF-b concentra- RESULTS tion at the onset, independenlty from T1D progression. Clinical features of pediatric patients with T1D These results show a differential pattern of circulating throughout the study. No statistical differences between TGF-b that discriminates between patients with or groups were found in age and BMI; however, they without spontaneous PR. Patients with PR do not have were found in terms of insulin dose, HbA1c values and a less aggressive T1D onset, but a real different evolu- in IDDAA1c values (Table 1). tion of their diabetes. Circulating TGF-b levels decrease during PR stage. Cir- Plasmatic concentration of betatrophin is increased in culating TGF-b concentration was determined in 10 pediatric patients with T1D. Plasma betatrophin levels (pg/ control subjects and in 22 patients with T1D. Samples mL) were significantly increased in patients with T1D at Translational Research 12 Villalba et al August 2019 Fig 1. Plasma levels of TGF-b in pediatric patients with T1D. A, Concentration of TGF-b (pg/mL) in plasma of control subjects and patients with T1D at different checkpoints (onset and first year of progression). Data pre- sented as plot box and whiskers (Tukey). (*P < 0.05, Mann-Whitney test). B, Circulating TGF-b concentration (pg/mL) in plasma of control subjects and patients with T1D at different checkpoints (onset, 6, and 12 months) grouped with and without spontaneous partial remission (PR) development at 6 months. Data presented as plot box and whiskers (Tukey). (*P < 0.05, Mann-Whitney test). Fig 2. Plasma levels of betatrophin in pediatric patients with T1D. A, Circulating betatrophin concentration (pg/ mL) in plasma of control subjects and patients with T1D at different checkpoints (onset, 6, 12, and 18 months of progression). Data presented as plot box and whiskers (Tukey). Statistical differences were found between patients and controls (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, Mann-Whitney test). B, Follow- up of the circulating plasma betatrophin concentration (pg/mL) of the patients with T1D in partial remission stage. C, Linear regression of the individual values of plasma betatrophin concentration (mg/dL) (Spearman r = ‒0.3118, P value = 0.0823). the 4 different checkpoints (Fig 2, A) when compared to and follow-up was performed during 18 months after control subjects, whereas no statistical differences were diagnosis. No statistical differences were found in BMI found between patients at different disease stages. How- between groups, although they were observed in insulin ever, 12 months after the onset of the disease a trend to dose, HbA1c and in IDDAA1c. No statistical differen- decrease betatrophin concentration was observed ces were found in circulating betatrophin levels in (P = 0.057). No statistical differences were found when plasma between the 4 different checkpoints in PR grouping separately patients with and without spontane- patients (Fig 2, B), although a tendency for betatrophin ous PR at 6 months. to decrease was observed during disease progression To determine betatrophin levels in spontaneous PR, 8 (P = 0.0823) (Fig 2, C). patients with T1D showing PR criteria at 6 months were The correlation between circulating betatrophin lev- selected from the initial group of 22 patients (Table 3) els with BMI was explored both in general T1D and Translational Research Volume 210 Villalba et al 13 Table 3. Clinical data for pediatric patients with T1D at disease onset, and at 6, 12, and 18 mo of disease progression included in the follow-up measurements of plasma betatrophin Onset 6 mo 12 mo 18 mo n 8 8 8 8 Gender (M/F) 5/3 5/3 5/3 5/3 Age (years, mean § SD) 9.63 § 3.78 10.13 § 3.78 10.63 § 3.78 11.13 § 3.78 BMI (kg/m2) 17.06 § 4.59 18.27 § 2.33 17.57 § 1.2 17.67 § 1.41 Insulin dose (UI/kg/day) 0.72 § 0.58 0.43 § 0.25 0.66 § 0.22 0.75 § 0.31 HbA1c (%) 10.26 § 1.66 6.84 § 0.90 7.86 § 1.10 8.23 § 1.04 HbA1c (mmol/mol) 89 § 18.1 51 § 9.8 62 § 12 66 § 11.4 IDDAA1C (%) 13.15 § 1.93 8.15 § 1.19 10.58 § 1.47 11.33 § 1.05 Data presented as mean § SD. No statistical differences were found in age between groups. Statistical differences were found in insulin (onset vs 6 mo: #, 6 mo vs 12 mo: *, 6 mo vs 18 mo: *); glycated hemoglobin (HbA1c) (onset vs 6 mo: #, onset vs 12 mo: *, onset vs 18 mo: *, 6 mo vs 12 mo: #, 12 mo vs 18 mo: #); and in insulin dose-adjusted HbA1c (IDDAA1c) (onset vs 6 mo: x, onset vs 12 mo: * and 6 mo vs 18 mo: x). Statistical differences calculated from Mann-Whitney test (*P < 0.05, # P < 0.01, x P < 0.001, < P < 0.0001). BMI, body mass index; HbA1c, glycated hemo- globin; IDDAA1c, insulin dose-adjusted HbA1c. PR patients as well as in control subjects (Fig 3). No Regulatory leukocyte subsets are biomarkers of T1D correlation was found between BMI-betatrophin levels onset and progression stages. No statistically significant at the onset stage in T1D patients or in PR patients. differences were found in age and BMI between groups Finally, At 18 months, a statistically significant posi- (Table 4). Lymphocyte subsets involved in different tive correlation was found between BMI-betatrophin immunoregulation strategies were studied, including levels both in general and in PR patients (P = 0.0047 regulatory T cells (Treg), both activated (aTreg) and and 0.0480, respectively). memory (mTreg), Th17 cells (which contain a regula- Immune response-related molecules are altered at the tory Th17 subset21), regulatory B cells (Breg), and reg- onset of T1D. Different molecules involved in immune ulatory Natural Killer cells (NKreg) (Fig 4). No response were analyzed as potential biomarkers. These correlation was found between these subsets (% and molecules were selected in basis of the altered expres- numbers) and the age of the subjects in the different sion in the pancreases from patients with T1D.11 One groups, ie, controls, onset, first year, and second year. of these molecules is HLA-G, considered an immuno- Different percentages of the Treg subset including modulatory molecule involved in tolerance and pro- both aTreg and mTreg were observed at each T1D posed as a pancreatic regulator.20 However, circulating stage (Fig 4, AD). The percentage of aTreg was sHLA-G did not reveal significant differences between increased during the first year of disease in compari- control subjects and patients at different stages son to the second year and control subjects (Fig 4, (Fig S1, A). To gain further knowledge within the non- B), whereas the percentage of mTreg was decreased classical HLA network, the expression of these mole- only at the onset when compared with control sub- cules was also measured in peripheral blood jects (Fig 4, D). In both cases the concentration was mononuclear cells (PBMCs) from patients with T1D. maintained along the different groups (Fig 4, A and Overexpressed mRNA levels of HLA-E were found in 4, C). The Th17 cell subset, which includes a specific PBMCs from patients at the onset (Fig S1, B) when and minority Th17 regulatory subset, showed an compared to control subjects. In contrast, mRNA levels increased percentage during the first year of progres- of HLA-F were not altered in PBMCs from patients at sion when compared to the second year (Fig 4, F). the onset when compared to control subjects (Fig S1, The corresponding cell concentration was main- C). The expression of other altered molecules such as tained during T1D progression, at levels similar to IL-8, TLR3, and CXCL1 was increased in PBMCs those found in control subjects (Fig 4, E). The Breg from newly diagnosed patients (Fig S2). A positive cell subset was found increased both in concentration correlation was found between the expression of 2 che- and in percentage during the first year of disease (Fig mokines involved in leukocyte recruitment, IL-8 and 4, G and H). Finally, the percentage of NKreg cells CXCL1 (Fig S3), being moderately positive correlated was increased during the second year when com- in control subjects (R2 = 0.8615) and strongly positive pared to the first year of disease (Fig 4, I and J). In correlated (R2 = 0.9498) in patients at the onset of summary, an increase in regulatory T, B and NK sub- T1D. The expression of other genes, such as CD36 and sets was found during T1D progression, reflecting LYZ, in PBMCs was not significantly different than the attempts to restore tolerance to self during these that of control subjects (Fig S2). early stages. Translational Research 14 Villalba et al August 2019 Fig 3. Correlation of betatrophin levels with BMI in pediatric patients with T1D at different stages of the dis- ease. Linear regression of circulating plasma betatrophin concentration (pg/mL) vs BMI (kg/m2) in patients with T1D and control subjects. A, Patients with T1D at the onset (Spearman r = ‒0.00226, P value = 0.9999). B, Patients who underwent partial remission (PR), at the onset of T1D (Spearman r = ‒0.1429, P value = 0.7520). C and D, Patients at 6 months of disease progression (Spearman r = 0.634, P value = 0.1705) and those who underwent PR (Spearman r = 0.3877, P value = 0.1009). E and F, Patients at 12 months of disease progression (Spearman r = 0.4895, P value = 0.1098), and those who underwent PR (Spearman r = 0.5, P value = 0.2667). G and H, Patients at 18 months of disease progression (Spearman r = 0.8, P value = 0.0047, **) and PR group (Spearman r = 0.7857, P value = 0.0480, *). I, Control group (Spearman r = ‒0.07692, P value = 0.8171). Translational Research Volume 210 Villalba et al 15 Table 4. Clinical data for controls, and patients at onset, first and second year of T1D progression included in lymphocyte subsets analysis Control Onset 1y 2y N 16 11 12 7 Gender (M/F) 9/7 6/5 3/9 1/6 Age (years, mean § SD) 8.58 § 4.42 8.69 § 5.16 10.20 § 3.87 10.01 § 2.78 BMI (kg/m2) 19.43 § 1.26 18.24 § 3.10 17.53 § 2.67 18.51 § 2.13 Insulin dose (UI/kg/day) ND 0.69 § 0.27 0.62 § 0.20 0.83 § 0.23 HbA1c (%) ND 8.87 § 1.98 7.86 § 1.17 7.82 § 1.68 HbA1c (mmol/mol) 73 §21.58 62 §12.75 62 §18.3 IDDAA1C (%) ND 10.11 § 13.21 8.93 § 11.79 7.09 § 15.25 Data presented as mean§SD. Statistical differences were found in BMI (control subjects vs patients with T1D during the first year: (*)). Statistical differences calculated using the Mann-Whitney test (*P < 0.05). ND, not determined. Low circulating monocyte count is associated with T1D decrease in B transitional high subset counts was found onset and second year of progression. Alterations in at the second year when compared to control subjects monocyte counts were found at the early stages of and to the first year of disease (Fig 6, E), but this T1D (Fig 5). Total monocyte count showed a trend to change was not reflected in the percentage (Fig 6, F). be lower at the onset of the disease when compared to Regarding B transitional low subpopulation, the control subjects, but at the second year of T1D pro- amount of these cells was lower at the second year of gression differences were significant (Fig 5, A and B). disease when compared to the first year (Fig 6, G and Within this monocyte family, the numbers of classical H). This subset includes functional regulatory B cells monocytes (CD14+CD16‒) confirmed these results and despite its role is not completely understood, their and also showed a decrease at the onset of the disease increase may reflect the attempts to restore self-toler- (Fig 5, C), but this was not reflected in the percentage ance during T1D early stages. (Fig 5, D). The nonclassical monocyte subset T lymphocyte subsets are quantitatively altered at the (CD14+CD16+) showed no statistical differences or onset and at early stages of diabetes progression. Be- tendencies between the different groups (data not cause T cells are the final effector cells in T1D, both ab shown). In summary, the concentration of total mono- and gd T cell populations were screened (Fig 7). The cytes and its major subpopulation, the classical concentration and percentage of ab T cell subpopula- CD14+CD16‒ monocyte subset, was diminished at the tion (Fig 7, A and B) were decreased at the second year early stages of diabetes. Since monocytes are precur- of disease when compared to control and other disease sors of antigen-presenting cells, their decrease in stages. Among different ab T cells subsets, only double periphery at the second year of disease progression positive T lymphocytes were decreased in counts at the suggests an active extravasation to target tissues, second year when compared to the first year of disease probably to contribute to the chronification of the (Fig 7, C) but not in percentage (Fig 7, D). Regarding autoimmune response. the gd CD4+ T cell subset, no differences were found B lymphocyte subsets are quantitatively altered at the among different groups (data not shown). The CD8+ gd onset and at early stages of T1D progression. The analysis subset was decreased in concentration at the first year of of B lymphocytes at different maturation stages, mem- progression when compared to the second year, and the ory/activation subsets, and B transitional lymphocytes, percentage tended to decrease during disease progres- revealed quantitative alterations during the first 2 years sion (Fig 7, E and F). In summary, alterations in total of disease progression (Fig 6). The concentration of ab and gd T cell subpopulations were observed during CD27+ B cells was increased at the first year of disease 2 years of T1D progression. when compared to the onset and to the second year of The different T lymphocyte maturation stages were disease. However, it was not reflected in the percentage determined and showed alterations at the onset and at (Fig 6, A and B). The total B transitional subset also the different stages of T1D (Figs 810). Only the total showed an increase in concentration during the first CD3+ CD4+ T lymphocyte population concentration year of disease when compared to the second year and was found decreased at the onset of T1D when com- to control subjects, but this alteration was not observed pared to control subjects and the first year of disease in the percentage (Fig 6, C and D). Within the B transi- (Fig 8, A and B). Within this population, the central tional population, alterations were found both in B memory (CM) CD27+ subset revealed alterations both transitional high and low subsets (Fig 6, EH), previ- in concentration and percentage. There was an increase ously referred as T1 and T2 in the literature. A in concentration in the second year when compared to Translational Research 16 Villalba et al August 2019 Fig 4. Concentration and percentage of regulatory lymphocyte subsets in peripheral blood from pediatric patients with T1D at different stages of the disease. Concentration (cells/mL) and percentage (%) of A and B, acti- vated T regulatory cells (aTreg), C and D, memory T regulatory cells (mTreg), E and F, Th17 cells, G and H, B regulatory cells (Breg), and I and J, Natural Killer regulatory cells (NKreg). White symbols represent control subjects, whereas black symbols represent patients with T1D at onset (dots), 1 year (squares) and 2 years (trian- gles) after diagnosis. (*P < 0.05, ***P < 0.001, ****P < 0.0001, Mann-Whitney test). Translational Research Volume 210 Villalba et al 17 Fig 5. Concentration and percentage of monocytes in peripheral blood from pediatric patients with T1D at dif- ferent stages of the disease. Concentration (cells/mL) and percentage (%) of A and B, total monocytes, and C and D, its major subset, classical monocytes. White symbols represent control subjects, whereas black symbols rep- resent patients with T1D at onset (dots), 1 year (squares) and 2 years (triangles) after diagnosis. (*P < 0.05, Mann-Whitney test). the first year of disease (Fig 8, C). Also, there was an Besides the CD4+ population, CM and EM in the increase in percentage at disease onset when compared CD8+ subsets were also altered (Fig 10). Total counts to control subjects, with a tendency to decrease with of CD3+ CD8+ T cells were decreased at the onset of progression of diabetes until a rate similar to control the disease when compared to control subjects, and group at second year (Fig 8, D). The PTK7+ subpopula- normalized after diagnosis (Fig 10, A and B). Regard- tion, included in the CD4+ naive subset, revealed an ing the CM subset, a decrease in counts and percent- increase in percentage during the second year of dis- age, was observed during the second year of ease (Fig 8, F). progression (Fig 10, C and D). The analysis of the The CD4+ T lymphocyte effector memory subsets CD8+ na€ıve cells subset showed a decrease in cell were analyzed (Fig 9). Total CD4+ effector cells number at the onset and during the first year of disease expressing the marker CD45RA (EMRA) subsets (Fig 10, E), in agreement with the data of CD3+ CD8+ showed a remarkable decrease in both concentration population (Fig 10, A). Moreover, a decrease in (Fig 9, A) and percentage at the onset of the disease (Fig EMRA CD8+ T cell counts (Fig 10, G) was observed, 9, B). Furthermore, this decrease in concentration was but not in percentage (Fig 10, H). This decrease in con- also observed in both CD4+ EMRA subsets: CD27+ (Fig centration was observed at T1D onset in the EMRA 9, C) and CD27‒ (Fig 9, E), but not in their percentage CD27+ subset (Fig 10, I), whereas in percentage, a (Fig 9, D and Fig 9, F, respectively). In addition, the decrease was found at the first year of the disease (Fig CD4+ EM cell subset revealed lower counts at disease 10, J). In summary, alterations in the CM and EM line- onset when compared to the first year of disease (Fig 9, ages of T lymphocytes and their maturation stages G). This is due to alterations in the CD4+ EM CD27+ have been detected at early T1D progression. All these subset (Fig 9, I). This effect was not reflected in percent- cell subsets are commonly found in the spleen and in age (Fig 9, H and Fig 9, J, respectively). the lymph nodes, and the decrease in peripheral blood Translational Research 18 Villalba et al August 2019 Fig 6. Concentration and percentage of B lymphocytes in peripheral blood from pediatric patients with T1D at different stages of the disease. Concentration (cells/mL) and percentage (%) of A and B, total CD27+ peripheral blood mononuclear cells (PBMCs), C and D, total B transitional lymphocytes, E and F, B transitional high, and G and H, B transitional low. White symbols represent control subjects, whereas black symbols represent patients with T1D at onset (dots), 1 year (squares) and 2 years (triangles) after diagnosis. (*P < 0.05, **P < 0.01, Mann- Whitney test). Translational Research Volume 210 Villalba et al 19 Fig 7. Concentration and percentage of ab and gd T lymphocytes in peripheral blood from pediatric patients with T1D at different stages of the disease. Concentration (cells/mL) and percentage (%) of A and B, total ab, C and D, its subset CD3+ double positive (DP), and E and F, gd CD8+. White symbols represent control subjects, whereas black symbols represent patients with T1D at onset (dots), 1 year (squares) and 2 years (triangles) after diagnosis. (*P < 0.05, Mann-Whitney test). of EM and EMRA T cells both in the CD4+ and the of secondary complications, and the discovery of optimal CD8+ T cell subsets at the onset could reflect the need checkpoints for potential therapies. Metabolic parame- for a compensatory mechanism, due to an active migra- ters are currently the most reliable biomarkers, and dur- tion to target tissue. ing disease progression, C-peptide levels are considered to reflect residual insulin storage. Although this is a good biomarker for endogenous insulin production and secre- tion, the sensitivity of the technique prevents the assess- DISCUSSION ment of low values22 and most pediatric patients show It is known that the lack of biomarkers of T1D stages undetectable C-peptide levels at disease onset.6 Thus, hinders the proper stratification patients, the prediction novel biomarkers for stratifying subjects and for Translational Research 20 Villalba et al August 2019 Fig 8. Concentration and percentage of CD4+ T lymphocyte subsets. Concentration (cells/mL) and percentage (%) of A and B, total CD3+CD4+, C and D, CD4+ CM CD27+ and E and F, its major subset PTK7+. White sym- bols represent control subjects, whereas black symbols represent patients with T1D at onset (dots), 1 year (squares) and 2 years (triangles) after diagnosis (*P < 0.05, Mann-Whitney test). immunomonitoring are needed. This article presents a plasma at the onset of pediatric T1D. Furthermore, screening of candidate biomarkers in pediatric patients those increased levels remain steady during the early with T1D, with special interest in the early stages. progression of the disease, including the PR stage. There are many and diverse immune biomarkers of Thus, circulating betatrophin levels in plasma do not T1D.23 In this pilot study, aimed at determining dif- distinguish PR stage. Our results of the correlation ferential molecular and cell patterns in children diag- between a metabolic parameter such as BMI and cir- nosed with T1D in our geographic area, potential culating betatrophin levels are in keeping with those candidates have been considered. Betatrophin, a described in T1D8 and T2D24 that suggest that hyper- promising biomarker in long-standing adult patients glycemia may be the pivotal point for betatrophin with T1D,8 showed a triplicated concentration in upregulation in diabetes. Translational Research Volume 210 Villalba et al 21 Fig 9. Concentration and percentage values of CD4+ and its effector memory (EM) subset, included in the T lymphocytes maturation stages. Values in concentration (cells/mL) and percentage (%) of A and B, total EMRA CD4+, C and D, CD4+ EMRA CD27+, E and F, CD4+ EMRA CD27‒, G and H, total CD4+ EM, and I and J, CD4+ EM CD27+. White symbols represent control subjects, whereas black symbols represent patients with T1D at onset (dots), 1 year (squares) and 2 years (triangles) after diagnosis (*P < 0.05, **P < 0.01, ****P < 0.0001, Mann-Whitney test). Translational Research 22 Villalba et al August 2019 Fig 10. Concentration and percentage values of CD8+ lymphocytes and their subsets, included in the T lympho- cytes maturation stages. Values in concentration (cells/mL) and percentage (%) of A and B, total CD3+CD8+, C and D, CD8+ CM CD27+, E and F, CD8+ Na€ıve CD27, G and H, total CD8+ EMRA, and I and J, its subset CD8+ EMRA CD27+. White symbols represent control subjects, whereas black symbols represent patients with T1D at onset (dots), 1 year (squares) and 2 years (triangles) after diagnosis (*P < 0.05, **P < 0.01, ***P < 0.001, Mann-Whitney test). Translational Research Volume 210 Villalba et al 23 Table 5. Summary of candidate biomarkers altered during pediatric T1D early progression Candidate biomarker Source Stage Outcome Betatrophin Plasma Onset, 6, 12, and 18 mo of progression Increased TGF-b Plasma Partial remission Decreased aTreg (%) Blood First year of progression Increased Breg (% and counts) Blood First year of progression Increased NKreg (%) Blood Second year of progression Increased Then, the potential of other immune mediators generation in primary lymphoid organs and by their whose expression was strongly altered in the pan- migration to the target tissue, ie, the pancreas in T1D. creases from patients with T1D11 was analyzed. Here The decrease of the percentage of mTreg at the onset we demonstrate for the first time a decrease in circu- of the disease in children is accompanied by a strong lating TGF-b during PR when compared to the onset. increase in aTreg at the first year. Since Tregs are cru- This candidate biomarker for PR distinguishes pediat- cial in self-tolerance, these data reflect the autoimmune ric patients until 1 year after diagnosis. Low TGF-b attack at T1D onset as mTregs are reduced. The levels in PR could reflect the transient recovery of increase in aTregs during the first year of disease, self-tolerance proposed at this stage.1 In fact, TGF-b which is also when the classical appearance of PR is increased in patients at the onset of T1D10 reflect- occurs, may reveal the attempts to restore self-toler- ing a response to autoimmunity activation and corre- ance. In this sense, a mathematical model explains that lating with the fact that hyperglycemia stimulates T1D onset is the consequence of an increase in effector TGF-b expression.25 Because many cells can secrete T lymphocytes over Treg and that the PR stage may be TGF-b, a deeper understanding of the mechanisms due to an inversion in the frequencies of these sub- involved in the decrease of plasma concentration dur- sets.28 As for Breg and NKreg cell subsets, their role in ing PR is needed. In this stage, the remaining b-cells T1D is not completely understood. This is the first are still able to produce enough insulin and, in some report showing an increase of Breg and NKreg in early cases, transient insulin-independence can be stages of pediatric T1D. Future studies may provide achieved. The identification of reliable biomarkers insight into the role of these cells in PR and T1D. would allow for the identification and monitorization We are well aware of the limitations of this study. of PR. Because there are no differences in TGF-b lev- Despite a relatively small sample size, the P value of els when comparing patients at PR and non PR stages the here proposed biomarkers  betatrophin, TGF-b at 6 and 12 months of evolution of the disease, at and regulatory T, B, and NK subsets  determines sta- present it would be useful for the monitoring of PR tistical differences. Furthermore, these candidates were for each particular patient. selected from previous data and in basis of their biolog- Additionally, lymphocyte cell subsets have been ical effect. Future analysis of “big data” obtained from used as biomarkers for several immune mediated dis- an independent cohort would be beneficial for both val- eases. One of the main advantages of using them is the idation of these candidate biomarkers and for the amount of given information due to the multiple screening of new ones. Nevertheless, the strength of parameters that can be analyzed in the sample, and its the study is the identification of immunologic altera- ease of tracking during disease progression. Lympho- tions in early stages of the disease, with special interest cyte regulatory subsets have been partially character- in the PR, an unexplored  and often undetected  ized in T1D. Since they are crucial in self-tolerance phase of T1D. In our cohort PR was evident at and show phenotypic, functional and migration altera- 6 months after diabetes onset. Thus, we plan to include tions in autoimmunity,26,27 this study aimed at deter- this time checkpoint for all patients and variables to be mining the changes in regulatory leukocyte subsets investigated in future studies. during the first 2 years of T1D in children. Alterations Overall, the results (summarized in Table 5) reveal were found in all regulatory leukocyte subsets both in the characterization of the changes in these parameters concentration and percentage, reflecting a robust sig- during the different early stages of T1D in children  nificance. Moreover, the alterations observed in one betatrophin, TGF-b and regulatory T, B and NK sub- variable can be due to compensatory mechanisms sets  that could be used in clinical practice to charac- undergone by other cell lineage subsets to accommo- terize the progression of T1D. Moreover, and because date the first change. Since lymphocyte subsets can PR may be an ideal stage for immunointervention, only be determined in peripheral blood at a time, these candidate biomarkers can be considered for clini- peripheral subsets are tightly regulated by their cal trials. 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