Department of Surgery, University of British Columbia (UBC), and BC Children's Hospital Research Institute (BCCHRI), Vancouver, British Columbia, Canada.
Department of Medicine and Centre for Heart Lung Innovation, UBC, and Prevention of Organ Failure (PROOF) Centre of Excellence, St. Paul's Hospital, Vancouver, British Columbia, Canada.
JCI Insight. 2019 Mar 21;4(6). doi: 10.1172/jci.insight.123879.
Multiple therapeutic strategies to restore immune regulation and slow type 1 diabetes (T1D) progression are in development and testing. A major challenge has been defining biomarkers to prospectively identify subjects likely to benefit from immunotherapy and/or measure intervention effects. We previously found that, compared with healthy controls, Tregs from children with new-onset T1D have an altered Treg gene signature (TGS), suggesting that this could be an immunoregulatory biomarker.
nanoString was used to assess the TGS in sorted Tregs (CD4+CD25hiCD127lo) or peripheral blood mononuclear cells (PBMCs) from individuals with T1D or type 2 diabetes, healthy controls, or T1D recipients of immunotherapy. Biomarker discovery pipelines were developed and applied to various sample group comparisons.
Compared with controls, the TGS in isolated Tregs or PBMCs was altered in adult new-onset and cross-sectional T1D cohorts, with sensitivity or specificity of biomarkers increased by including T1D-associated SNPs in algorithms. The TGS was distinct in T1D versus type 2 diabetes, indicating disease-specific alterations. TGS measurement at the time of T1D onset revealed an algorithm that accurately predicted future rapid versus slow C-peptide decline, as determined by longitudinal analysis of placebo arms of START and T1DAL trials. The same algorithm stratified participants in a phase I/II clinical trial of ustekinumab (αIL-12/23p40) for future rapid versus slow C-peptide decline.
These data suggest that biomarkers based on measuring TGSs could be a new approach to stratify patients and monitor autoimmune activity in T1D.
JDRF (1-PNF-2015-113-Q-R, 2-PAR-2015-123-Q-R, 3-SRA-2016-209-Q-R, 3-PDF-2014-217-A-N), the JDRF Canadian Clinical Trials Network, the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (UM1AI109565 and FY15ITN168), and BCCHRI.
目前有多种治疗策略可用于恢复免疫调节并减缓 1 型糖尿病（T1D）的进展，其中一个主要挑战是定义生物标志物，以便前瞻性地识别可能从免疫疗法中受益的受试者，并评估干预效果。我们之前发现，与健康对照者相比，新发 T1D 患儿的调节性 T 细胞（Treg）具有改变的 Treg 基因特征（TGS），这表明这可能是一种免疫调节生物标志物。
采用 nanoString 技术检测 T1D 患者、2 型糖尿病患者、健康对照者或接受免疫治疗的 T1D 患者的分选 Treg（CD4+CD25hiCD127lo）或外周血单个核细胞（PBMC）中的 TGS。开发并应用了生物标志物发现管道，用于各种样本组比较。
与对照组相比，成人新发和横断面 T1D 队列中的分离 Treg 或 PBMC 中的 TGS 发生改变，通过将 T1D 相关 SNP 纳入算法，可提高生物标志物的灵敏度或特异性。TGS 在 T1D 与 2 型糖尿病之间存在差异，表明存在疾病特异性改变。T1D 发病时的 TGS 测量结果揭示了一种算法，该算法可通过 START 和 T1DAL 试验安慰剂组的纵向分析，准确预测未来 C 肽快速下降与缓慢下降的情况。同一算法对乌司奴单抗（αIL-12/23p40）的 I/II 期临床试验的参与者进行了分层，以预测未来 C 肽快速下降与缓慢下降的情况。
这些数据表明，基于测量 TGS 的生物标志物可能是一种新的方法，可以对患者进行分层，并监测 T1D 中的自身免疫活性。
JDRF（1-PNF-2015-113-Q-R、2-PAR-2015-123-Q-R、3-SRA-2016-209-Q-R、3-PDF-2014-217-A-N）、JDRF 加拿大临床试验网络、美国国立卫生研究院过敏和传染病研究所（UM1AI109565 和 FY15ITN168）和不列颠哥伦比亚省癌症研究中心。
