Aparicio Andrea, Sun Zheng, Gold Diane R, Litonjua Augusto A, Weiss Scott T, Lee-Sarwar Kathleen, Liu Yang-Yu
medRxiv. 2023 Nov 13:2023.11.13.23298467. doi: 10.1101/2023.11.13.23298467.
The influence of genotype on defining the human gut microbiome has been extensively studied, but definite conclusions have not yet been found. To fill this knowledge gap, we leverage data from children enrolled in the Vitamin D Antenatal Asthma Reduction Trial (VDAART) from 6 months to 8 years old. We focus on a pool of 12 genes previously found to be associated with the gut microbiome in independent studies, establishing a Bonferroni corrected significance level of p-value < 2.29 × 10 . We identified significant associations between SNPs in the FHIT gene (known to be associated with obesity and type 2 diabetes) and obesity-related microbiome features, and the children's BMI through their childhood. Based on these associations, we defined a set of SNPs of interest and a set of taxa of interest. Taking a multi-omics approach, we integrated plasma metabolome data into our analysis and found simultaneous associations among children's BMI, the SNPs of interest, and the taxa of interest, involving amino acids, lipids, nucleotides, and xenobiotics. Using our association results, we constructed a quadripartite graph where each disjoint node set represents SNPs in the FHIT gene, microbial taxa, plasma metabolites, or BMI measurements. Network analysis led to the discovery of patterns that identify several genetic variants, microbial taxa and metabolites as new potential markers for obesity, type 2 diabetes, or insulin resistance risk.
基因型对人类肠道微生物群定义的影响已得到广泛研究,但尚未得出明确结论。为填补这一知识空白,我们利用了参与维生素D产前哮喘减少试验(VDAART)的6个月至8岁儿童的数据。我们重点关注先前在独立研究中发现与肠道微生物群相关的12个基因组合,设定了经邦费罗尼校正的p值显著性水平<2.29×10 。我们发现FHIT基因中的单核苷酸多态性(已知与肥胖和2型糖尿病相关)与肥胖相关的微生物群特征以及儿童整个童年时期的体重指数之间存在显著关联。基于这些关联,我们定义了一组感兴趣的单核苷酸多态性和一组感兴趣的分类群。采用多组学方法,我们将血浆代谢组数据纳入分析,发现儿童体重指数、感兴趣的单核苷酸多态性和感兴趣的分类群之间存在同时关联,涉及氨基酸、脂质、核苷酸和外源性物质。利用我们的关联结果,我们构建了一个四方图,其中每个不相交的节点集分别代表FHIT基因中的单核苷酸多态性、微生物分类群、血浆代谢物或体重指数测量值。网络分析导致发现了一些模式,这些模式将几种基因变异、微生物分类群和代谢物确定为肥胖、2型糖尿病或胰岛素抵抗风险的新潜在标志物。