Midya V, Lane J M, Gennings C, Torres-Olascoaga L A, Wright R O, Arora M, Téllez-Rojo M M, Eggers S
Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Center for Research on Nutrition and Health, National Institute of Public Health, Cuernavaca, Mexico.
medRxiv. 2023 May 24:2023.05.18.23290127. doi: 10.1101/2023.05.18.23290127.
Many analytical methods used in gut microbiome research focus on either single bacterial taxa or the whole microbiome, ignoring multi-bacteria relationships (microbial cliques). We present a novel analytical approach to identify multiple bacterial taxa within the gut microbiome of children at 9-11 years associated with prenatal Pb exposure.
Data came from a subset of participants (n=123) in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) 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 2-taxa microbial clique that included and , and a 3-taxa clique that added . Increasing second-trimester Pb exposure was associated with significantly increased odds of having the 2-taxa microbial clique below the 50 percentile relative abundance (OR=1.03,95%CI[1.01-1.05]). In an analysis of Pb concentration at or above vs. below the United States and Mexico guidelines for child Pb exposure, odds of the 2-taxa clique in low abundance were 3.36(95%CI[1.32-8.51]) and 6.11(95%CI[1.87-19.93]), respectively. Trends were similar with the 3-taxa clique but not statistically significant.
Using a novel combination of machine-learning and causal-inference, MiCA identified a significant association between second-trimester Pb exposure and reduced abundance of a probiotic microbial clique within the gut microbiome in late childhood. Pb exposure levels at the guidelines for child Pb poisoning in the United States, and Mexico are not sufficient to protect against the potential loss of probiotic benefits.
肠道微生物组研究中使用的许多分析方法要么侧重于单一细菌分类群，要么侧重于整个微生物组，而忽略了多细菌关系（微生物团）。我们提出了一种新颖的分析方法，以识别9至11岁儿童肠道微生物组中与产前铅暴露相关的多种细菌分类群。
数据来自肥胖、生长、环境和社会压力源编程研究（PROGRESS）队列中的一部分参与者（n = 123）。在妊娠中期和晚期测量母体全血中的铅浓度。对9至11岁时采集的粪便样本进行宏基因组测序，以评估肠道微生物组。使用一种新颖的分析方法，即微生物共现分析（MiCA），我们将机器学习算法与基于随机化的推理相结合，首先识别可预测产前铅暴露的微生物团，然后估计产前铅暴露与微生物团丰度之间的关联。
对于孕中期铅暴露，我们识别出一个包含[具体细菌1]和[具体细菌2]的双细菌分类群微生物团，以及一个添加了[具体细菌3]的三细菌分类群微生物团。孕中期铅暴露增加与双细菌分类群微生物团相对丰度低于第50百分位数的几率显著增加相关（OR = 1.03，95%CI[1.01 - 1.05]）。在一项关于美国和墨西哥儿童铅暴露指南规定的铅浓度高于或低于该浓度的分析中，低丰度双细菌分类群的几率分别为3.36（95%CI[1.32 - 8.51]）和6.11（9 %CI[1.87 - 19.93]）。三细菌分类群的趋势相似，但无统计学意义。
通过机器学习和因果推理的新颖结合，MiCA识别出孕中期铅暴露与儿童晚期肠道微生物组中益生菌微生物团丰度降低之间存在显著关联。美国和墨西哥儿童铅中毒指南规定的铅暴露水平不足以防止益生菌益处的潜在丧失。
