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产前铅暴露与儿童后期有益肠道微生物共生体丰度降低有关:使用微生物共现分析(MiCA)的研究。

Prenatal Lead Exposure Is Associated with Reduced Abundance of Beneficial Gut Microbial Cliques in Late Childhood: An Investigation Using Microbial Co-Occurrence Analysis (MiCA).

机构信息

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States.

Center for Research on Nutrition and Health, National Institute of Public Health, Cuernavaca 62100, Mexico.

出版信息

Environ Sci Technol. 2023 Nov 7;57(44):16800-16810. doi: 10.1021/acs.est.3c04346. Epub 2023 Oct 25.

Abstract

Many analytical methods used in gut microbiome research focus on either single bacterial taxa or the whole microbiome, ignoring multibacteria relationships (microbial cliques). We present a novel analytical approach to identify microbial cliques within the gut microbiome of children at 9-11 years associated with prenatal lead (Pb) exposure. Data came from a subset of participants ( = 123) in the Programming Research in Obesity, Growth, Environment and Social Stressors cohort. Pb concentrations were measured in maternal whole blood from the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the gut microbiome. Using a novel analytical approach, Microbial Co-occurrence Analysis (MiCA), we paired a machine learning algorithm with randomization-based inference to first identify microbial cliques that were predictive of prenatal Pb exposure and then estimate the association between prenatal Pb exposure and microbial clique abundance. With second-trimester Pb exposure, we identified a two-taxa microbial clique that included and and a three-taxa clique that also included . Increasing second-trimester Pb exposure was associated with significantly increased odds of having the two-taxa microbial clique below the median relative abundance (odds ratio (OR) = 1.03, 95% confidence interval (CI) [1.01-1.05]). Using a novel combination of machine learning and causal inference, MiCA identified a significant association between second-trimester Pb exposure and the reduced abundance of a probiotic microbial clique within the gut microbiome in late childhood.

摘要

许多用于肠道微生物组研究的分析方法要么专注于单一细菌分类群,要么关注整个微生物组,而忽略了多细菌之间的关系(微生物集团)。我们提出了一种新的分析方法,用于识别 9-11 岁儿童肠道微生物组中与产前铅(Pb)暴露相关的微生物集团。该数据来自肥胖、生长、环境和社会应激源编程研究队列的一部分参与者(n = 123)。在妊娠第二和第三个三个月时,从母亲全血中测量 Pb 浓度。在 9-11 岁时收集的粪便样本进行了宏基因组测序,以评估肠道微生物组。我们使用一种新的分析方法——微生物共生分析(MiCA),将机器学习算法与基于随机化的推断相结合,首先识别出可预测产前 Pb 暴露的微生物集团,然后估计产前 Pb 暴露与微生物集团丰度之间的关联。在妊娠第二期 Pb 暴露的情况下,我们鉴定出一个包含 和 的两细菌微生物集团,以及一个还包含 的三细菌集团。第二期 Pb 暴露的增加与两细菌微生物集团的中位数相对丰度以下的可能性显著增加相关(比值比(OR)= 1.03,95%置信区间(CI)[1.01-1.05])。使用机器学习和因果推理的新组合,MiCA 确定了妊娠第二期 Pb 暴露与肠道微生物组中益生菌微生物集团丰度降低之间的显著关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c803/10634322/558a81f58f32/es3c04346_0001.jpg

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