Exploring causal associations between nuclear magnetic resonance biomarkers and colorectal cancer risk.

IF 3.3 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM
Qingyi Zhou, Lichun Yang, Peiyu Zhu, Yutong Wang, Zilu Zhang, Liang Chu
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引用次数: 0

Abstract

Background: Emerging evidence shows significant differences in plasma metabolites between colorectal cancer (CRC) patients and healthy controls. However, previous observational studies have been limited by small sample sizes and single sample sources, leading to an incomplete understanding of these metabolites' causal roles in CRC. This study systematically evaluated the causal relationships between 325 nuclear magnetic resonance (NMR) biomarkers and CRC risk using Mendelian randomization (MR), supplemented by colocalization analysis and an independent validation dataset to confirm key biomarkers.

Methods: A genome-wide association study (GWAS) was conducted in a cohort of 250,341 participants from the UK Biobank. MR analysis identified NMR biomarkers with significant causal relationships with CRC. Colocalization analysis was then performed, revealing five biomarkers with high colocalization probabilities (PPH4 > 0.8). These findings were validated in an independent Finnish dataset to confirm the consistency of causal relationships and colocalization signals.

Results: MR analysis identified 28 NMR biomarkers with significant causal associations with CRC risk (P_fdr < 0.05). Colocalization analysis highlighted five biomarkers with strong colocalization signals (PPH4 > 0.8), including Omega-6 fatty acids, Omega-6 to total fatty acids ratio, Omega-3 fatty acids, Linoleic acid to total fatty acids percentage, and Degree of unsaturation. Notably, in the Finnish validation dataset, Linoleic acid to total fatty acids percentage demonstrated a significant causal association with CRC (OR 0.77, 95% CI 0.67-0.87, P = 7.5 × 10-5, P_fdr = 3.8 × 10-4) while maintaining a high colocalization probability (PPH4 > 0.8), reinforcing its role as a key causal biomarker.

Conclusions: This study provides the first comprehensive assessment of NMR biomarkers in relation to rectal cancer risk, identifying linoleic acid to total fatty acids percentage as a key causal biomarker. Additionally, omega-6 to omega-3 ratio, omega-6 to polyunsaturated fatty acids percentage, omega-3 to polyunsaturated fatty acids percentage, and degree of unsaturation were also identified, sharing genetic loci with CRC.

探讨核磁共振生物标志物与结直肠癌风险之间的因果关系。
背景:新出现的证据表明,结直肠癌(CRC)患者和健康对照者的血浆代谢物存在显著差异。然而,以往的观察性研究受到小样本量和单一样本来源的限制,导致对这些代谢物在结直肠癌中的因果作用的了解不完整。本研究采用孟德尔随机化方法系统评估了325种核磁共振(NMR)生物标志物与结直肠癌风险之间的因果关系,并辅以共定位分析和独立验证数据集来确定关键生物标志物。方法:一项全基因组关联研究(GWAS)在来自英国生物银行的250,341名参与者中进行。核磁共振分析发现核磁共振生物标志物与结直肠癌有显著的因果关系。然后进行共定位分析,发现5个具有高共定位概率的生物标志物(PPH4 > 0.8)。这些发现在一个独立的芬兰数据集中得到验证,以确认因果关系和共定位信号的一致性。结果:MR分析确定了28个与结直肠癌风险有显著因果关系的核磁共振生物标志物(P_fdr 0.8),包括Omega-6脂肪酸、Omega-6与总脂肪酸比率、Omega-3脂肪酸、亚油酸与总脂肪酸百分比和不饱和程度。值得注意的是,在芬兰的验证数据集中,亚油酸占总脂肪酸百分比与CRC显示出显著的因果关系(OR 0.77, 95% CI 0.67-0.87, P = 7.5 × 10-5, P_fdr = 3.8 × 10-4),同时保持较高的共定位概率(PPH4 > 0.8),强化了其作为关键因果生物标志物的作用。结论:本研究首次提供了与直肠癌风险相关的核磁共振生物标志物的综合评估,确定亚油酸占总脂肪酸的百分比是一个关键的因果生物标志物。此外,还发现了omega-6与omega-3的比例、omega-6与多不饱和脂肪酸的百分比、omega-3与多不饱和脂肪酸的百分比和不饱和程度,与CRC具有相同的基因位点。
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
Metabolomics
Metabolomics 医学-内分泌学与代谢
CiteScore
6.60
自引率
2.80%
发文量
84
审稿时长
2 months
期刊介绍: Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to: metabolomic applications within man, including pre-clinical and clinical pharmacometabolomics for precision medicine metabolic profiling and fingerprinting metabolite target analysis metabolomic applications within animals, plants and microbes transcriptomics and proteomics in systems biology Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.
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