Urinary based biomarkers identification and genetic profiling in Parkinson's disease: a systematic review of metabolomic studies.

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in bioinformatics Pub Date : 2025-03-10 eCollection Date: 2025-01-01 DOI:10.3389/fbinf.2025.1513790
Neetu Rani Dhiman, Surbhi Singh, Royana Singh, Anand Kumar, Varun Kumar Singh, Abhishek Pathak, Rameshwar Nath Chaurasia, Vijay Nath Mishra, Niraj Kumar Srivastava, Swati Sahu, Nikhil Pandey, Deepika Joshi
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引用次数: 0

Abstract

Background: Parkinson's disease is a complex, age-related, neurodegenerative disease associated with dopamine deficiency and both motor and nonmotor deficits. Therapeutic pathways remain challenging in Parkinson's disease due to the low accuracy of early diagnosis, the difficulty in monitoring disease progression, and the limited availability of treatment options.

Objectives: Few data are present to identify urinary biomarkers for various ailments, potentially aiding in the diagnosis and tracking of illness progression in individuals with Parkinson's disease. Thus, the analysis of urinary metabolomic biomarkers (UMB) for early and mid-stage idiopathic Parkinson's disease (IPD) is the main goal of this systematic review.

Methods: For this study, six electronic databases were searched for articles published up to 23 February 2024: PubMed, Ovid Medline, Embase, Scopus, Science Direct, and Cochrane. 5,377 articles were found and 40 articles were screened as per the eligibility criteria. Out of these, 7 controlled studies were selected for this review. Genetic profiling for gene function and biomarker interactions between urinary biomarkers was conducted using the STRING and Cytoscape database.

Results: A total of 40 metabolites were identified to be related to the early and mid-stage of the disease pathology out of which three metabolites, acetyl phenylalanine (a subtype of phenylalanine), tyrosine and kynurenine were common and most significant in three studies. These metabolites cause impaired dopamine synthesis along with mitochondrial disturbances and brain energy metabolic disturbances which are considered responsible for neurodegenerative disorders. Furoglycine, Cortisol, Hydroxyphenylacetic acid, Glycine, Tiglyglycine, Aminobutyric acid, Hydroxyprogesterone, Phenylacetylglutamine, and Dihydrocortisol were also found commonly dysregulated in two of the total 7 studies. 158 genes were found which are responsible for the occurrence of PD and metabolic regulation of the corresponding biomarkers from our study.

Conclusion: The current review identified acetyl phenylalanine (a subtype of phenylalanine), tyrosine and kynurenine as potential urinary metabolomic biomarkers for diagnosing PD and identifying disease progression.

背景:帕金森病是一种复杂的、与年龄相关的神经退行性疾病,伴有多巴胺缺乏、运动和非运动障碍。由于早期诊断准确率低、难以监测疾病进展以及治疗方案有限,帕金森病的治疗途径仍具有挑战性:目前很少有数据能确定各种疾病的尿液生物标志物,这可能有助于诊断和跟踪帕金森病患者的病情发展。因此,分析早期和中期特发性帕金森病(IPD)的尿液代谢组学生物标志物(UMB)是本系统综述的主要目标:本研究在六个电子数据库中检索了截至 2024 年 2 月 23 日发表的文章:PubMed、Ovid Medline、Embase、Scopus、Science Direct 和 Cochrane。共找到 5377 篇文章,根据资格标准筛选出 40 篇文章。本综述从中筛选出 7 项对照研究。利用 STRING 和 Cytoscape 数据库对尿液生物标志物之间的基因功能和生物标志物相互作用进行了基因分析:结果:共发现 40 种代谢物与疾病早期和中期的病理变化有关,其中乙酰苯丙氨酸(苯丙氨酸的一种亚型)、酪氨酸和犬尿氨酸这三种代谢物在三项研究中最为常见和重要。这些代谢物会导致多巴胺合成障碍、线粒体紊乱和脑能量代谢障碍,被认为是神经退行性疾病的罪魁祸首。在总共 7 项研究中,有 2 项研究发现呋喃甘氨酸、皮质醇、羟基苯乙酸、甘氨酸、惕格甘氨酸、氨基丁酸、羟孕酮、苯乙酰谷氨酰胺和二氢皮质醇也普遍存在失调。从我们的研究中发现了 158 个基因,这些基因对发生帕金森病和相应生物标志物的代谢调节负责:本综述发现乙酰苯丙氨酸(苯丙氨酸的一种亚型)、酪氨酸和犬尿氨酸是诊断帕金森病和确定疾病进展的潜在尿液代谢组学生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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