Kulecka Maria, Jaworski Paweł, Zeber-Lubecka Natalia, Bałabas Aneta, Piątkowska Magdalena, Czarnowski Paweł, Frączek Barbara, Tarnowski Wiesław, Mikula Michał, Ostrowski Jerzy
Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, 02-781 Warsaw, Poland.
Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland.
Nutrients. 2025 Jul 14;17(14):2320. doi: 10.3390/nu17142320.
: Our aim was to create a new method for analyzing metagenomics data, named the gut microbiome obesity index, using a set of taxa/biological functions that correlated with BMI. : A total of 109 obese patients (73 women and 36 men, median BMI 43.0 kg/m), 87 healthy control (HC) individuals (39 females and 48 males, median BMI 22.7 kg/m), and 109 esports players (five females and 104 males, median BMI 23.0 kg/m) were included in the study. To conduct metagenomic and metabolomic analyses, DNA and selected metabolites were isolated from fecal samples and used for whole-genome shotgun sequencing and gas chromatography/mass spectrometry, respectively. : Compared with HCs and esports players, obese patients with a BMI > 40 kg/m had a significantly higher alpha diversity, as analyzed by the Shannon index, and significant dissimilarities in beta diversity. Both richness and diversity measures were correlated with BMI. Compared with HCs and esports players, 12 differential bacteria were found in the overall obesity group and 42 were found in those with a BMI > 40 kg/m. Most of the altered species belonged to the family. When the logarithmic relationship of the sums of the bacteria correlated with BMI was calculated to establish a taxonomic health index, it better differentiated between the obesity groups than a standard analytical pipeline; however, it did not differentiate between the HC and the BMI < 35 kg/m obesity group. Therefore, we created a functional index based on BMI-associated biological pathways, which differentiated between all obesity groups. : Of the obesity indices used to distinguish between healthy and obese microbiota analyzed in this study, a function-based index was more useful than a taxonomy-based index. We believe that gut microbiome indexes could be useful as part of routine metagenomics evaluations. However, an index developed in one geographical area might not be applicable to individuals in a different region and, therefore, further studies should develop separate indices for different populations or geographical regions rather than relying on a single index.
我们的目标是创建一种分析宏基因组学数据的新方法，即肠道微生物群肥胖指数，该方法使用一组与体重指数（BMI）相关的分类群/生物学功能。本研究纳入了109名肥胖患者（73名女性和36名男性，BMI中位数为43.0kg/m²）、87名健康对照（HC）个体（39名女性和48名男性，BMI中位数为22.7kg/m²）以及109名电子竞技选手（5名女性和104名男性，BMI中位数为23.0kg/m²）。为了进行宏基因组学和代谢组学分析，从粪便样本中分离出DNA和选定的代谢物，分别用于全基因组鸟枪法测序和气相色谱/质谱分析。与HC个体和电子竞技选手相比，BMI>40kg/m²的肥胖患者经香农指数分析显示其α多样性显著更高，β多样性也存在显著差异。丰富度和多样性指标均与BMI相关。与HC个体和电子竞技选手相比，在总体肥胖组中发现了12种差异细菌，在BMI>40kg/m²的患者中发现了42种。大多数改变的物种属于该科。当计算与BMI相关的细菌总和的对数关系以建立分类健康指数时，它比标准分析流程能更好地区分肥胖组；然而，它无法区分HC个体和BMI<35kg/m²的肥胖组。因此，我们基于与BMI相关的生物学途径创建了一个功能指数，该指数能够区分所有肥胖组。在本研究中用于区分健康和肥胖微生物群的肥胖指数中，基于功能的指数比基于分类学的指数更有用。我们认为肠道微生物群指数作为常规宏基因组学评估的一部分可能会很有用。然而，在一个地理区域开发的指数可能不适用于不同区域个体，因此，未来研究应为不同人群或地理区域开发单独的指数，而不是依赖单一指数。
Cochrane Database Syst Rev. 2016-8-18
Cochrane Database Syst Rev. 2005-7-20
Cochrane Database Syst Rev. 2025-7-10
Cochrane Database Syst Rev. 2013-4-30
Cochrane Database Syst Rev. 2021-4-19
Cochrane Database Syst Rev. 2014-1-17
Cochrane Database Syst Rev. 2014-8-8
Cochrane Database Syst Rev. 2018-2-6
Gigascience. 2025-1-6
Microorganisms. 2024-8-26
NPJ Biofilms Microbiomes. 2024-9-8
Microbiome. 2023-8-18
Diabetes Metab Syndr Obes. 2022-12-29
Zotero 插件