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从身体成分和局部脂肪到广泛代谢表型的因果途径:一项孟德尔随机化研究。

Causal Pathways from Body Components and Regional Fat to Extensive Metabolic Phenotypes: A Mendelian Randomization Study.

机构信息

Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China.

Institute for Medical Dataology, Shandong University, Jinan, People's Republic of China.

出版信息

Obesity (Silver Spring). 2020 Aug;28(8):1536-1549. doi: 10.1002/oby.22857.

Abstract

OBJECTIVE

The aim of this study was to explore the causal effects and pathways from body components to extensive metabolic phenotypes.

METHODS

Summarized data including 24 metabolic phenotypes from 10 consortiums were used to perform univariate, multivariable, and bidirectional Mendelian randomization analysis based on the network design.

RESULTS

For metabolically related biomarkers, a 1-SD increase in body fat mass (BFM) was robustly associated with increased fasting insulin, systolic blood pressure, diastolic blood pressure, and urate and decreased high-density lipoprotein cholesterol levels. For metabolically related diseases, the odds ratios and 95% CIs of a 1-SD increase in BFM were 1.76 (1.37 to 2.25) for type 2 diabetes mellitus (T2DM), 1.11 (1.09 to 1.13) for hypertension, 1.40 (1.25 to 1.57) for coronary artery disease, 1.41 (1.25 to 1.59) for myocardial infarction, 1.25 (1.12 to 1.40) for ischemic stroke, and 1.62 (1.02 to 2.57) for gout. The effects of body fat on diseases were mediated by extensive intermediate biomarkers, including blood pressure, lipids, glycemic traits, and urate. Regional fats had a similar effect with body fat in both absolute and relative scales, whereas fat-free components increased only the risk of T2DM 1.73 (1.11 to 2.68) and chronic kidney disease 1.51 (1.11 to 2.06).

CONCLUSIONS

Several potential pathways were found and confirmed the tremendous benefits of fat-lowering measures, including lowering of various regional fats. Future policies or interventions should focus more on the role of body fat.

摘要

目的

本研究旨在探讨身体成分与广泛代谢表型之间的因果关系和途径。

方法

利用来自 10 个联盟的 24 种代谢表型的汇总数据,基于网络设计进行单变量、多变量和双向孟德尔随机化分析。

结果

对于代谢相关生物标志物,体脂肪量(BFM)每增加 1 个标准差,与空腹胰岛素、收缩压、舒张压和尿酸升高以及高密度脂蛋白胆固醇水平降低显著相关。对于代谢相关疾病,BFM 每增加 1 个标准差,2 型糖尿病(T2DM)的比值比(OR)及其 95%可信区间(CI)为 1.76(1.37 至 2.25),高血压为 1.11(1.09 至 1.13),冠心病为 1.40(1.25 至 1.57),心肌梗死为 1.41(1.25 至 1.59),缺血性卒中和痛风分别为 1.25(1.12 至 1.40)和 1.62(1.02 至 2.57)。身体脂肪对疾病的影响是通过广泛的中间生物标志物介导的,包括血压、血脂、血糖特征和尿酸。区域脂肪在绝对值和相对值上与体脂肪具有相似的影响,而无脂肪成分仅增加 T2DM 的风险 1.73(1.11 至 2.68)和慢性肾脏病 1.51(1.11 至 2.06)。

结论

发现了几种潜在的途径,并证实了降低脂肪的措施具有巨大的益处,包括降低各种区域脂肪。未来的政策或干预措施应更加关注身体脂肪的作用。

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