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Comparative Proteomic and Metabolomic Analyses of Plasma Reveal the Novel Biomarker Panels for Thyroid Dysfunction

生物标志物 代谢组学 甲状腺 蛋白质组学 内科学 医学 生物标志物发现 内分泌学 生物信息学 肿瘤科 生物 生物化学 基因
作者
Haodong Xia,Yaohan Li,Shengzhi Liu,Haote Han,Chaoting Zhou,Luyang Wang,Qiangan Jing,Jingkui Tian,Xiangmin Tong,Ying Wang,Wei Zhu
出处
期刊:Frontiers in bioscience [Bioscience Research Institute Pte. Ltd.]
卷期号:27 (3) 被引量:9
标识
DOI:10.31083/j.fbl2703090
摘要

Thyroid dysfunction, including hypothyroidism (THO) and hyperthyroidism (THE), commonly arise from pathological processes in the thyroid gland. The current diagnosis of thyroid dysfunction varies because of the age and sex of the patients. The aim of this study was to explore novel candidate biomarker panels for hypothyroidism and hyperthyroidism screening with mass spectrometry and bioinformatics.Plasma samples were collected from 15 THE patients, 9 THO patients, and 15 healthy controls. Data Independent Acquisition(DIA)-based proteomic and untargeted metabolomic analyses were performed to identify novel biomarker panels for THO and THE patients. Finally, three candidate biomarkers were verified by ELISA in 34 samples.A total of 2738 proteins and 6103 metabolites were identified, and 173 proteins and 2487 metabolites were found to be differentially expressed among the THE, THO and control groups. The results of the ensemble feature selection, K-means clustering and least absolute shrinkage and selection operator (LASSO) regression model showed that two proteins (C4-A and C3/C5 convertase) combined with two metabolites (L-arginine and L-proline), and proteins (APOL1 and ITIH4) combined with metabolites (cortisol, and cortisone) identified by plasma proteomics and metabolomics could help distinguish THO and THE patients from healthy controls, respectively.This study identified and verified two pairs of biomarker panels that can be used to distinguish THE and THO patients regardless of age and sex. Consequently, our findings represent a comprehensive analysis of thyroid dysfunction plasma, which is significant for clinical diagnosis.
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