Predicting The Early Risk Of Ophthalmopathy In Graves' Disease Patients Using Tcr Repertoire

CLINICAL AND TRANSLATIONAL MEDICINE(2020)

引用 2|浏览0
暂无评分
摘要
Background: Graves' ophthalmopathy (GO), the common extrathyroidal manifestation in Graves' hyperthyroidism (GH), often has an unsatisfactory therapeutic effect due to late diagnosis. Methods: Firstly, we proposed a novel score termed TCR Clonal expansion and chaos Score (TCS) to characterize VJ. TCS score equals to the ratio between clonal expansion of TCR V-J combination and chaos of peptide similarity. Then, we sequenced the RNA transcripts from the complementarity determining region 3 (CDR3) of TCR Vβ from 100 peripheral blood samples, including 43 and 57 stable GH. Random forest method was applied to select candidate features with the best performance to classify and GH. Lastly, this model was applied in an independent validation dataset consisting of 18 stable samples and 17 samples who progressed to in the follow up visit. Findings: The leave-one-out cross validation showed this model with a sensitivity of 87.88% and a specificity of 81.08% to differentiate from stable GH. And it achieved a sensitivity and specificity of 70.59% and 72.22% for prediction progression in GH. Specifically, 12 of the 17 patients who were as developed symptoms of eyelid swelling, chemosis or proptosis in a median of 6.5 months (4-9.75 months, IQR). In addition, GO-free survival analysis demonstrated that predicted GO patients (n = 17) were significant difference with predicted GH patients (n = 18) in progression (P = 0.015, log-rank test). Interpretation: Our finding provides a proof of concept for diagnosis and prognosis using TCR repertoire and may help develop novel prophylactic strategy for and other autoimmune diseases. Funding Statement: This work was supported by the National Key R&D Program of China (grant NO. 2018YFC1311500 (B.S.), 2017YFC0907500 (K.Y.) and 2018YFC0910400 (K.Y.)), National Science Foundation of China (NSFC) (grant NO. 81670725 (B.S.), 81500690 (Y.W.), 31671372 (K.Y.), 61702406 (X.Y.)), the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University, China (grant NO. XJTU1AF-CRF-2017-001 (B.S.)), Natural Science Foundation of Shaanxi Province (2018JM70990 (Y.W.)), Key Research and Development Project of Shaanxi Province (grant NO. 2017ZDXM-SF-060 (B.S.)), the Fundamental Research Funds for the Central Universities (1191329875 (Y.W.)), China Postdoctoral Science Foundation (224646(Y.W.)). Declaration of Interests: The authors have declared that no conflict of interest exists. Ethics Approval Statement: This study was approved by the Ethic Committee of the First Affiliated Hospital of Xi’an Jiaotong University (KYLLSL-2015-004-01). Informed consent was sought from all patients before screening and study entry.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要