Suppr超能文献

横断面代谢亚组与英国生物库中心血管代谢合并症的 10 年随访。

Cross-sectional metabolic subgroups and 10-year follow-up of cardiometabolic multimorbidity in the UK Biobank.

机构信息

Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, Australia.

Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.

出版信息

Sci Rep. 2022 May 21;12(1):8590. doi: 10.1038/s41598-022-12198-1.

Abstract

We assigned 329,908 UK Biobank participants into six subgroups based on a self-organizing map of 51 biochemical measures (blinded for clinical outcomes). The subgroup with the most favorable metabolic traits was chosen as the reference. Hazard ratios (HR) for incident disease were modeled by Cox regression. Enrichment ratios (ER) of incident multi-morbidity versus randomly expected co-occurrence were evaluated by permutation tests; ER is like HR but captures co-occurrence rather than event frequency. The subgroup with high urinary excretion without kidney stress (HR = 1.24) and the subgroup with the highest apolipoprotein B and blood pressure (HR = 1.52) were associated with ischemic heart disease (IHD). The subgroup with kidney stress, high adiposity and inflammation was associated with IHD (HR = 2.11), cancer (HR = 1.29), dementia (HR = 1.70) and mortality (HR = 2.12). The subgroup with high liver enzymes and triglycerides was at risk of diabetes (HR = 15.6). Multimorbidity was enriched in metabolically favorable subgroups (3.4 ≤ ER ≤ 4.0) despite lower disease burden overall; the relative risk of co-occurring disease was higher in the absence of obvious metabolic dysfunction. These results provide synergistic insight into metabolic health and its associations with cardiovascular disease in a large population sample.

摘要

我们根据 51 项生化指标的自组织图(针对临床结果进行了盲法处理),将 329908 名英国生物银行参与者分为六组亚群。选择代谢特征最有利的亚群作为参考。通过 Cox 回归模型对疾病发病的风险比(HR)进行建模。通过置换检验评估发病多种疾病与随机预期共同发生的富集比(ER);ER 类似于 HR,但捕捉共同发生而不是事件频率。尿中无肾脏应激的排泄量高(HR=1.24)和载脂蛋白 B 和血压最高的亚群(HR=1.52)与缺血性心脏病(IHD)相关。具有肾脏应激、高肥胖和炎症的亚群与 IHD(HR=2.11)、癌症(HR=1.29)、痴呆(HR=1.70)和死亡率(HR=2.12)相关。肝脏酶和甘油三酯高的亚群易患糖尿病(HR=15.6)。尽管整体疾病负担较低,但在代谢良好的亚群中,多种疾病的发生更为丰富(3.4≤ER≤4.0);在没有明显代谢功能障碍的情况下,同时发生疾病的相对风险更高。这些结果为在大型人群样本中代谢健康及其与心血管疾病的关联提供了协同的深入了解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bdc/9124207/6957bb24ca07/41598_2022_12198_Fig1_HTML.jpg

相似文献

3
Lifestyle trajectories and ischaemic heart diseases: a prospective cohort study in UK Biobank.
Eur J Prev Cardiol. 2023 Mar 27;30(5):393-403. doi: 10.1093/eurjpc/zwad001.
7
Metabolic profile predicts incident cancer: A large-scale population study in the UK Biobank.
Metabolism. 2023 Jan;138:155342. doi: 10.1016/j.metabol.2022.155342. Epub 2022 Oct 29.
8
Role of depression in the development of cardiometabolic multimorbidity: Findings from the UK Biobank study.
J Affect Disord. 2022 Dec 15;319:260-266. doi: 10.1016/j.jad.2022.09.084. Epub 2022 Sep 23.

引用本文的文献

1
An unsupervised cluster analysis of multimorbidity patterns in older adults in Shenzhen, China.
Front Public Health. 2025 Jun 6;13:1557721. doi: 10.3389/fpubh.2025.1557721. eCollection 2025.
2
Personalized Profiling of Lipoprotein and Lipid Metabolism Based on 1018 Measures from Combined Quantitative NMR and LC-MS/MS Platforms.
Anal Chem. 2024 Dec 31;96(52):20362-20370. doi: 10.1021/acs.analchem.4c03229. Epub 2024 Dec 16.
3
Unsupervised clustering identified clinically relevant metabolic syndrome endotypes in UK and Taiwan Biobanks.
iScience. 2024 Apr 25;27(7):109815. doi: 10.1016/j.isci.2024.109815. eCollection 2024 Jul 19.
5
Novel subgroups of obesity and their association with outcomes: a data-driven cluster analysis.
BMC Public Health. 2024 Jan 9;24(1):124. doi: 10.1186/s12889-024-17648-1.
6
Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic.
Int J Obes (Lond). 2023 Jun;47(6):453-462. doi: 10.1038/s41366-023-01281-w. Epub 2023 Feb 23.
7
Metabolic profile-based subgroups can identify differences in brain volumes and brain iron deposition.
Diabetes Obes Metab. 2023 Jan;25(1):121-131. doi: 10.1111/dom.14853. Epub 2022 Sep 21.
8

本文引用的文献

2
Characterisation, identification, clustering, and classification of disease.
Sci Rep. 2021 Mar 8;11(1):5405. doi: 10.1038/s41598-021-84860-z.
7
Chronic Kidney Disease and Coronary Artery Disease: JACC State-of-the-Art Review.
J Am Coll Cardiol. 2019 Oct 8;74(14):1823-1838. doi: 10.1016/j.jacc.2019.08.1017.
9
Atherosclerosis.
Nat Rev Dis Primers. 2019 Aug 16;5(1):56. doi: 10.1038/s41572-019-0106-z.
10
The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis.
J Hepatol. 2019 Oct;71(4):793-801. doi: 10.1016/j.jhep.2019.06.021. Epub 2019 Jul 4.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验