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通路水平代谢组学分析表明,碳代谢是爱沙尼亚生物银行中发生高血压的关键因素。

Pathway level metabolomics analysis identifies carbon metabolism as a key factor of incident hypertension in the Estonian Biobank.

作者信息

Hiie Liis, Kolde Anastassia, Pervjakova Natalia, Reigo Anu, Abner Erik, Võsa Urmo, Esko Tõnu, Fischer Krista, Palta Priit, Kronberg Jaanika

机构信息

Estonian Genome Centre, Institute of Genomics, University of Tartu, Riia 23b, 51010, Tartu, Estonia.

Institute of Mathematics and Statistics, University of Tartu, Narva 18, 51009, Tartu, Estonia.

出版信息

Sci Rep. 2025 Mar 12;15(1):8470. doi: 10.1038/s41598-025-92840-w.

DOI:10.1038/s41598-025-92840-w
PMID:40069276
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11897224/
Abstract

The purpose of this study was to find metabolic changes associated with incident hypertension in the volunteer-based Estonian Biobank. We used a subcohort of the Estonian Biobank where metabolite levels had been measured by mass-spectrometry (LC-MS, Metabolon platform). We divided annotated metabolites of 989 individuals into KEGG pathways, followed by principal component analysis of metabolites in each pathway, resulting in a dataset of 91 pathway components. Next, we defined incident hypertension cases and controls based on electronic health records, resulting in a dataset of 101 incident hypertension cases and 450 controls. We used Cox proportional hazards models and replicated the results in a separate cohort of the Estonian Biobank, assayed with LC-MS dataset of the Broad platform and including 582 individuals. Our results show that body mass index and a component of the carbon metabolism KEGG pathway are associated with incident hypertension in both discovery and replication cohorts. We demonstrate that a high-dimensional dataset can be meaningfully reduced into informative pathway components that can subsequently be analysed in an interpretable way, and replicated in a metabolomics dataset from a different platform.

摘要

本研究的目的是在基于志愿者的爱沙尼亚生物银行中寻找与新发高血压相关的代谢变化。我们使用了爱沙尼亚生物银行的一个亚队列,其中代谢物水平已通过质谱法(液相色谱-质谱联用,Metabolon平台)进行测量。我们将989名个体的注释代谢物分为KEGG通路,然后对每个通路中的代谢物进行主成分分析,得到一个包含91个通路成分的数据集。接下来,我们根据电子健康记录定义新发高血压病例和对照,得到一个包含101例新发高血压病例和450例对照的数据集。我们使用Cox比例风险模型,并在爱沙尼亚生物银行的另一个队列中重复结果,该队列用布罗德平台的液相色谱-质谱联用数据集进行检测,包括582名个体。我们的结果表明,体重指数和碳代谢KEGG通路的一个成分在发现队列和重复队列中均与新发高血压相关。我们证明,一个高维数据集可以有意义地简化为信息丰富的通路成分,随后可以以可解释的方式进行分析,并在来自不同平台的代谢组学数据集中进行重复。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/952b/11897224/84180b6e6156/41598_2025_92840_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/952b/11897224/8a98aebb7724/41598_2025_92840_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/952b/11897224/84180b6e6156/41598_2025_92840_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/952b/11897224/8a98aebb7724/41598_2025_92840_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/952b/11897224/84180b6e6156/41598_2025_92840_Fig2_HTML.jpg

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KEGG: biological systems database as a model of the real world.京都基因与基因组百科全书(KEGG):作为现实世界模型的生物系统数据库。
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PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration.PathIntegrate:基于通路的多组学数据整合的多元建模方法。
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