Amplification-free electrochemical biosensor detection of circulating microRNA to identify drug-induced liver injury

检出限 生物传感器 介电谱 生物标志物 肝损伤 药品 分子诊断学 和平号-122 丙氨酸转氨酶 毒品检测 材料科学 色谱法 生物医学工程 化学 小RNA 医学 药理学 生物 纳米技术 电化学 生物信息学 内科学 电极 生物化学 基因 物理化学
作者
Appan Roychoudhury,James W. Dear,Maïwenn Kersaudy-Kerhoas,Till T. Bachmann
出处
期刊:Biosensors and Bioelectronics [Elsevier]
卷期号:231: 115298-115298 被引量:20
标识
DOI:10.1016/j.bios.2023.115298
摘要

Drug-induced liver injury (DILI) is a major challenge in clinical medicine and drug development. There is a need for rapid diagnostic tests, ideally at point-of-care. MicroRNA 122 (miR-122) is an early biomarker for DILI which is reported to increase in the blood before standard-of-care markers such as alanine aminotransferase activity. We developed an electrochemical biosensor for diagnosis of DILI by detecting miR-122 from clinical samples. We used electrochemical impedance spectroscopy (EIS) for direct, amplification free detection of miR-122 with screen-printed electrodes functionalised with sequence specific peptide nucleic acid (PNA) probes. We studied the probe functionalisation using atomic force microscopy and performed elemental and electrochemical characterisations. To enhance the assay performance and minimise sample volume requirements, we designed and characterised a closed-loop microfluidic system. We presented the EIS assay's specificity for wild-type miR-122 over non-complementary and single nucleotide mismatch targets. We successfully demonstrated a detection limit of 50 pM for miR-122. Assay performance could be extended to real samples; it displayed high selectivity for liver (miR-122 high) comparing to kidney (miR-122 low) derived samples extracted from murine tissue. Finally, we successfully performed an evaluation with 26 clinical samples. Using EIS, DILI patients were distinguished from healthy controls with a ROC-AUC of 0.77, a comparable performance to qPCR detection of miR-122 (ROC-AUC: 0.83). In conclusion, direct, amplification free detection of miR-122 using EIS was achievable at clinically relevant concentrations and in clinical samples. Future work will focus on realising a full sample-to-answer system which can be deployed for point-of-care testing.
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