Investigating Causal Links between Metabolite Profiles and Ulcerative Colitis: A Bidirectional Mendelian Randomization Study.

IF 1.1 Q4 ENGINEERING, BIOMEDICAL
Journal of Medical Signals & Sensors Pub Date : 2025-09-01 eCollection Date: 2025-01-01 DOI:10.4103/jmss.jmss_16_25
Parvin Zarei, Zoha Kamali, Ammar Hassanzadeh Keshteli, Peyman Adibi Sedeh, Ahmad Vaez
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引用次数: 0

Abstract

Background: While metabolic biomarkers are known to play a significant role in the development of ulcerative colitis (UC), the exact causal relationships between them remain uncertain and warrant further investigations. Here we report a bidirectional two-sample Mendelian randomization (MR) study to evaluate causal relationships between 503 blood metabolites and UC.

Methods: We used genome-wide association study (GWAS) data on blood metabolite levels from two separate studies on European individuals (n = 8299 and 24,925). In addition, for UC, we utilized GWAS data from the same ancestry, including 417,932 participants, comprising 5371 UC cases and 412,561 controls. We employed the inverse variance weighted method for our discovery stage of MR analyses. Then, we used other methods, including MR-Egger, weighted median, weighted mode, simple mode, MR-pleiotropy residual sum and outlier, heterogeneity, and pleiotropy tests for sensitivity analyses to further validate our findings and assess the robustness of our results.

Results: Our study suggests that total lipids in small high-density lipoprotein levels (S.HDL.L) are marginal significant positive associated with the development of UC (odds ratio = 1.167, 95% confidence interval: 0.998-1.364, P = 0.051). In addition, UC did not have a statistically significant effect on the metabolites.

Conclusions: Total lipids in S.HDL.L may offer a potential trend as valuable circulating metabolic biomarkers for the screening and prevention of UC in clinical practice. In addition, they could serve as potential candidate molecules for elucidating the mechanisms underlying UC and for identifying suitable drug targets.

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研究代谢物谱与溃疡性结肠炎之间的因果关系:一项双向孟德尔随机研究。
背景:虽然已知代谢生物标志物在溃疡性结肠炎(UC)的发展中发挥重要作用,但它们之间的确切因果关系仍不确定,需要进一步研究。在这里,我们报告了一项双向双样本孟德尔随机化(MR)研究,以评估503种血液代谢物与UC之间的因果关系。方法:我们使用了来自欧洲个体(n = 8299和24,925)的两项独立研究的血液代谢物水平的全基因组关联研究(GWAS)数据。此外,对于UC,我们利用了来自相同祖先的GWAS数据,包括417,932名参与者,包括5371例UC病例和412,561例对照。我们在MR分析的发现阶段采用了反方差加权法。然后,我们使用其他方法,包括MR-Egger、加权中位数、加权模式、简单模式、mr -多效性残差和异常值、异质性和多效性检验进行敏感性分析,以进一步验证我们的发现并评估我们结果的稳健性。结果:我们的研究表明,总脂小密度脂蛋白水平(S.HDL.L)与UC的发展呈边缘显著正相关(优势比= 1.167,95%可信区间:0.998-1.364,P = 0.051)。此外,UC对代谢物的影响没有统计学意义。结论:在临床实践中,高密度脂蛋白总脂可能成为筛查和预防UC的有价值的循环代谢生物标志物。此外,它们可以作为潜在的候选分子来阐明UC的机制和确定合适的药物靶点。
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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来源期刊
Journal of Medical Signals & Sensors
Journal of Medical Signals & Sensors ENGINEERING, BIOMEDICAL-
CiteScore
2.30
自引率
0.00%
发文量
53
审稿时长
33 weeks
期刊介绍: JMSS is an interdisciplinary journal that incorporates all aspects of the biomedical engineering including bioelectrics, bioinformatics, medical physics, health technology assessment, etc. Subject areas covered by the journal include: - Bioelectric: Bioinstruments Biosensors Modeling Biomedical signal processing Medical image analysis and processing Medical imaging devices Control of biological systems Neuromuscular systems Cognitive sciences Telemedicine Robotic Medical ultrasonography Bioelectromagnetics Electrophysiology Cell tracking - Bioinformatics and medical informatics: Analysis of biological data Data mining Stochastic modeling Computational genomics Artificial intelligence & fuzzy Applications Medical softwares Bioalgorithms Electronic health - Biophysics and medical physics: Computed tomography Radiation therapy Laser therapy - Education in biomedical engineering - Health technology assessment - Standard in biomedical engineering.
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