Development of a sensitive disease-screening model using comprehensive circulating microRNA profiles in dogs: A pilot study

IF 1.9 Q2 AGRICULTURE, DAIRY & ANIMAL SCIENCE Veterinary and Animal Science Pub Date : 2024-11-26 DOI:10.1016/j.vas.2024.100414
Kohei Omura , Kaori Ide , Masashi Takahashi , Yu Furusawa , Masanori Kobayashi , Yuichi Miyagawa , Aki Fujiwara-Igarashi , Takahiro Teshima , Yoshiaki Kubo , Akiko Yasuda , Karin Yoshida , Noriyuki Hayakawa , Masato Kobayashi , Yasuyuki Momoi
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Abstract

In the veterinary field, the utility of disease-identification models that use comprehensive circulating microRNA (miRNA) profiles produced through measurements based on next-generation sequencing (NGS) remains unproven. To integrate NGS technology with automated machine learning (autoML) to create a comprehensive circulating miRNA profile and to assess the clinical utility of a disease-screening model derived from this profile. The study involved dogs diagnosed with or being treated for various diseases, including tumors, across multiple veterinary clinics (n = 254), and healthy dogs without apparent diseases (n = 91). miRNA was extracted from EDTA-treated plasma, and a comprehensive analysis was conducted of one million reads per sample using NGS. Then autoML technology was applied to develop a diagnostic model based on miRNA. Among these models, the one with the highest performance was chosen for evaluation. The diagnostic model, based on the comprehensive circulating miRNA profile developed in this study, achieved an AUC score of 0.89, with a sensitivity of 85 % and a specificity of 88 % for the disease samples. The miRNA-based diagnostic model demonstrated high sensitivity for disease groups and has the potential to be an effective screening test. This study indicates that a comprehensive miRNA profile in dog plasma could serve as a highly sensitive blood biomarker.
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利用狗的综合循环microRNA谱建立敏感的疾病筛选模型:一项初步研究
在兽医领域,使用基于下一代测序(NGS)测量产生的综合循环microRNA (miRNA)谱的疾病识别模型的效用尚未得到证实。将NGS技术与自动机器学习(autoML)相结合,创建一个全面的循环miRNA谱,并评估由该谱衍生的疾病筛查模型的临床应用。该研究涉及多个兽医诊所(n = 254)诊断患有或正在治疗各种疾病(包括肿瘤)的狗,以及没有明显疾病的健康狗(n = 91)。从edta处理的血浆中提取miRNA,并使用NGS对每个样本进行100万reads的综合分析。然后应用autoML技术建立基于miRNA的诊断模型。在这些模型中,选择性能最高的模型进行评价。该诊断模型基于本研究开发的综合循环miRNA谱,对疾病样本的AUC评分为0.89,灵敏度为85%,特异性为88%。基于mirna的诊断模型显示出对疾病组的高敏感性,并有可能成为一种有效的筛查试验。这项研究表明,狗血浆中全面的miRNA谱可以作为一种高度敏感的血液生物标志物。
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来源期刊
Veterinary and Animal Science
Veterinary and Animal Science Veterinary-Veterinary (all)
CiteScore
3.50
自引率
0.00%
发文量
43
审稿时长
47 days
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